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@ARTICLE{2011,
  author = {Cebrail \v{k}flikli and Ali Gezer},
  title = {Self similarity analysis via fractional Fourier transform},
  journal = {Simulation Modelling Practice and Theory},
  year = {2011},
  volume = {19},
  pages = {986 - 995},
  number = {3},
  __markedentry = {[Sagnik]},
  doi = {DOI: 10.1016/j.simpat.2010.12.009},
  issn = {1569-190X},
  keywords = {Fractional Fourier transform},
  owner = {Sagnik},
  timestamp = {2011.02.21},
  url = {http://www.sciencedirect.com/science/article/B6X3C-51TYF4Y-1/2/bc73b7d672c12841c16505a0a2593c01}
}

@ARTICLE{emph[U+05BA]gen2009,
  author = {Mehmet Tankut \emph{[U+05BA]}gen and Ercan Engin Kuruoglu and Diego
	Herranz},
  title = {Astrophysical image separation by blind time-frequency source separation
	methods},
  journal = {Digital Signal Processing},
  year = {2009},
  volume = {19},
  pages = {360 - 369},
  number = {2},
  __markedentry = {[Sagnik]},
  doi = {DOI: 10.1016/j.dsp.2007.12.003},
  issn = {1051-2004},
  keywords = {Cosmic microwave background radiation},
  owner = {Sagnik},
  timestamp = {2011.02.21},
  url = {http://www.sciencedirect.com/science/article/B6WDJ-4RKMJ23-2/2/750215eb691a8f6c19f04788c2baa3a4}
}

@ARTICLE{A1999,
  author = {A, Cichocki and J, Karhunen and W, Kasprzak and R, Vigario},
  title = {Neural networks for blind separation with unknown number of sources
	- An adaptive algorithm based on neuromimetic architecture},
  journal = {Neurocomputing},
  year = {1999},
  volume = {24},
  pages = {55--93},
  number = {1},
  doi = {10.1016/S0925-2312(98)00091-5},
  keywords = {blind separation, image processing, Neural networks, Signal Reconstruction,
	Unsupervised learning},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{A2002,
  author = {V. David S\emph{[U+1BA3]}hez A},
  title = {Frontiers of research in BSS/ICA},
  journal = {Neurocomputing},
  year = {2002},
  volume = {49},
  pages = {7 - 23},
  number = {1-4},
  __markedentry = {[Sagnik]},
  doi = {DOI: 10.1016/S0925-2312(02)00533-7},
  issn = {0925-2312},
  keywords = {Blind source separation (BSS)},
  owner = {Sagnik},
  timestamp = {2011.02.21},
  url = {http://www.sciencedirect.com/science/article/B6V10-45M6G4R-8/2/a7e5f6e6907308951f88090f58a3e2b6}
}

@ARTICLE{Abe1995,
  author = {Abe, Sumiyoshi and Sheridan, John T.},
  title = {{Almost-Fourier} and {almost-Fresnel} transformations},
  journal = {Optics Communications},
  year = {1995},
  volume = {113},
  pages = {385--388},
  number = {4--6},
  month = jan,
  abstract = {Based on the special affine Fourier transformation {(SAFT)}, which
	is an extension of the fractional Fourier transformation, the small
	deviations from the perfect optical operations on wave functions
	are treated in a unified way. As simple and instructive examples,
	the {almost-Fourier} and {almost-Fresnel} transformations are constructed
	explicitly. The present investigation shows transformations which
	include the small imperfections of optical instruments can be developed
	within the framework of linear theory.},
  doi = {10.1016/0030-4018(94)00521-U},
  issn = {0030-4018},
  owner = {Sagnik},
  timestamp = {2012.02.23},
  url = {http://www.sciencedirect.com/science/article/pii/003040189400521U}
}

@ARTICLE{Abed-Meraim1997,
  author = {{Abed-Meraim}, K. and Qiu, W. and Hua, Y.},
  title = {Blind system identification},
  journal = {Proceedings of the {IEEE}},
  year = {1997},
  volume = {85},
  pages = {1310--1322},
  number = {8},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Abrard2005,
  author = {Abrard, F. and Deville, Y.},
  title = {A time-frequency blind signal separation method applicable to underdetermined
	mixtures of dependent sources},
  journal = {Signal Processing},
  year = {2005},
  volume = {85},
  pages = {1389--1403},
  number = {7},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Abrard2008,
  author = {Fr\emph{[U+9929]}ric Abrard and Yannick Deville and Johan Thomas},
  title = {Blind partial separation of underdetermined convolutive mixtures
	of complex sources based on differential normalized kurtosis},
  journal = {Neurocomputing},
  year = {2008},
  volume = {71},
  pages = {2071 - 2086},
  number = {10-12},
  note = {Neurocomputing for Vision Research; Advances in Blind Signal Processing},
  __markedentry = {[Sagnik]},
  doi = {DOI: 10.1016/j.neucom.2007.07.033},
  issn = {0925-2312},
  keywords = {Convolutive mixture},
  owner = {Welcome},
  timestamp = {2011.02.09}
}

@ARTICLE{Achard2005,
  author = {Achard, S. and Jutten, C.},
  title = {Identifiability of post-nonlinear mixtures},
  journal = {Signal Processing Letters, {IEEE}},
  year = {2005},
  volume = {12},
  pages = {423--426},
  number = {5},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Achard2001,
  author = {Achard, S. and Pham, {D.T.} and Jutten, C.},
  title = {Blind source separation in post nonlinear mixtures},
  booktitle = {Proc. Int. Workshop on Independent Component Analysis and Blind Signal
	Separation {(ICA2001)}},
  year = {2001},
  pages = {295--300},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Adelmann1998,
  author = {Holger G Adelmann},
  title = {Butterworth equations for homomorphic filtering of images},
  journal = {Computers in Biology and Medicine},
  year = {1998},
  volume = {28},
  pages = {169 - 181},
  number = {2},
  __markedentry = {[Sagnik]},
  doi = {DOI: 10.1016/S0010-4825(98)00004-3},
  issn = {0010-4825},
  keywords = {Homomorphic filter},
  owner = {Sagnik},
  timestamp = {2011.05.25},
  url = {http://www.sciencedirect.com/science/article/pii/S0010482598000043}
}

@INPROCEEDINGS{Akay1997,
  author = {Akay, M. and Mello, C.},
  title = {Wavelets for biomedical signal processing},
  booktitle = {Engineering in Medicine and Biology Society, 1997. Proceedings of
	the 19th Annual International Conference of the {IEEE}},
  year = {1997},
  volume = {6},
  pages = {2688--2691},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@BOOK{Aldous1985,
  title = {Fourier Series and Integrals},
  publisher = {Academic Press},
  year = {1985},
  editor = {Dym, H. and {McKean}, H. P.},
  author = {Aldous, David and Tong, Y. L.},
  edition = {1},
  month = oct,
  isbn = {0122264517},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Alieva1999,
  author = {Alieva, T. and Bastiaans, {M.J.}},
  title = {Self-imaging in first-order optical systems},
  journal = {Optics and Optoelectronics: Theory, Devices and Applications, {OP}
	Nijhawan, {AK} Gupta, {AK} Musla, and K. Singh, {eds.(Narosa}, New
	Delhi, 1998)},
  year = {1999},
  volume = {1},
  pages = {126--131},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Alieva1999a,
  author = {Alieva, T. and Bastiaans, {M.J.}},
  title = {{Radon-Wigner} transform for optical field analysis},
  journal = {Optics and Optoelectronics, Theory, Devices and Applications, Proc.
	{ICOL}},
  year = {1999},
  volume = {98},
  pages = {132--135},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@BOOK{Almeida2006,
  title = {Nonlinear source separation},
  publisher = {Morgan \& Claypool Publishers},
  year = {2006},
  author = {Almeida, Luis B.},
  abstract = {The purpose of this lecture book is to present the state of the art
	in nonlinear blind source separation, in a form appropriate for students,
	researchers and developers. Source separation deals with the problem
	of recovering sources that are observed in a mixed condition. When
	we have little knowledge about the sources and about the mixture
	process, we speak of blind source separation. Linear blind source
	separation is a relatively well studied subject, however nonlinear
	blind source separation is still in a less advanced stage, but has
	seen several significant developments in the last few years. This
	publication reviews the main nonlinear separation methods, including
	the separation of post-nonlinear mixtures, and the {MISEP}, ensemble
	learning and {kTDSEP} methods for generic mixtures. These methods
	are studied with a significant depth. A historical overview is also
	presented, mentioning most of the relevant results, on nonlinear
	blind source separation, that have been presented over the years.},
  isbn = {9781598290301},
  keywords = {Blind source separation, Computers / Data Transmission Systems / General,
	Nonlinear theories, Technology \& Engineering / Electrical, Technology
	\& Engineering / Signals \& Signal Processing, Technology \& Engineering
	/ Telecommunications},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@BOOK{Almeida2006a,
  title = {Nonlinear Source Separation},
  publisher = {Morgan \& Claypool Publishers, USA},
  year = {2006},
  author = {Luis B. Almeida},
  __markedentry = {[Sagnik]},
  owner = {Sagnik},
  timestamp = {2011.03.07}
}

@ARTICLE{Almeida1994,
  author = {Almeida, Luis B},
  title = {The fractional Fourier transform and time-frequency representations},
  journal = {Signal Processing, IEEE Transactions on},
  year = {1994},
  volume = {42},
  pages = {3084--3091},
  number = {11},
  publisher = {IEEE}
}

@ARTICLE{Amari1996,
  author = {Amari, S. and Cichocki, A. and Yang, {H.H.} and others},
  title = {A new learning algorithm for blind signal separation},
  journal = {Advances in neural information processing systems},
  year = {1996},
  pages = {757--763},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Amari1997,
  author = {Amari, S. and Douglas, {S.C.} and Cichocki, A. and Yang, {H.H.}},
  title = {Multichannel blind deconvolution and equalization using the natural
	gradient},
  booktitle = {Signal Processing Advances in Wireless Communications, 1997 First
	{IEEE} Signal Processing Workshop on},
  year = {1997},
  pages = {101--104},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Amari1997c,
  author = {Amari, S. and Douglas, {S.C.} and Cichocki, A. and Yang, {H.H.}},
  title = {Novel on-line adaptive learning algorithms for blind deconvolution
	using the natural gradient approach},
  booktitle = {in Proc. {SYSID}, Kitakyushu},
  year = {1997},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Amari1997b,
  author = {Amari, Shun-ichi and Douglas, Scott C and Cichocki, Andrzej and Yang,
	Howard H},
  title = {Novel On-line Adaptive Learning Algorithms for Blind Deconvolution
	using the Natural Gradient Approach},
  journal = {In Proceedings {SYSID}, Kitakyushu},
  year = {1997},
  volume = {3},
  pages = {1057---1062},
  owner = {Sagnik},
  timestamp = {2012.02.23},
  url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.52.6203}
}

@ARTICLE{Amari1999,
  author = {Amari, {S.I.}},
  title = {Natural gradient learning for over-and under-complete bases in {ICA}},
  journal = {Neural Computation},
  year = {1999},
  volume = {11},
  pages = {1875--1883},
  number = {8},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Amari1998a,
  author = {Amari, {S.I.}},
  title = {Natural gradient works efficiently in learning},
  journal = {Neural computation},
  year = {1998},
  volume = {10},
  pages = {251--276},
  number = {2},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Amari1997a,
  author = {Amari, {S.I.} and Chen, {T.P.} and Cichocki, A.},
  title = {Stability analysis of learning algorithms for blind source separation},
  journal = {Neural Networks},
  year = {1997},
  volume = {10},
  pages = {1345--1351},
  number = {8},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Amari1998,
  author = {Amari, {S.I.} and Cichocki, A.},
  title = {Adaptive blind signal processing-neural network approaches},
  journal = {Proceedings of the {IEEE}},
  year = {1998},
  volume = {86},
  pages = {2026--2048},
  number = {10},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Amari1993,
  author = {Amari, {S.I.} and Murata, N.},
  title = {Statistical theory of learning curves under entropic loss criterion},
  journal = {Neural Computation},
  year = {1993},
  volume = {5},
  pages = {140--153},
  number = {1},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Amari2000,
  author = {Amari, {S.I.} and Park, H. and Fukumizu, K.},
  title = {Adaptive method of realizing natural gradient learning for multilayer
	perceptrons},
  journal = {Neural Computation},
  year = {2000},
  volume = {12},
  pages = {1399--1409},
  number = {6},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Andremph[U+9812]ossi2010,
  author = {Andr\emph{[U+9812]}ossi and Alok Singh and Marc Sevaux},
  title = {A metaheuristic for the fixed job scheduling problem under spread
	time constraints},
  journal = {Computers \& Operations Research},
  year = {2010},
  volume = {37},
  pages = {1045 - 1054},
  number = {6},
  __markedentry = {[Sagnik]},
  doi = {DOI: 10.1016/j.cor.2009.09.007},
  issn = {0305-0548},
  keywords = {Fixed job scheduling},
  owner = {Welcome},
  timestamp = {2011.02.13},
  url = {http://www.sciencedirect.com/science/article/B6VC5-4X8RCTK-1/2/da9ae621205313170cdee2a3b5c9a5cd}
}

@ARTICLE{Anemuller2003,
  author = {Anem\"uller, J. and Sejnowski, {T.J.} and Makeig, S.},
  title = {Complex independent component analysis of frequency-domain electroencephalographic
	data},
  journal = {Neural Networks},
  year = {2003},
  volume = {16},
  pages = {1311--1323},
  number = {9},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Antipolis2008,
  author = {Antipolis, Sophia},
  title = {Repr\'esentations parcimonieuses: de la S\'eparation de Sources au
	Compressed Sensing},
  journal = {Sophia},
  year = {2008},
  owner = {Sagnik},
  shorttitle = {Repr\'esentations parcimonieuses},
  timestamp = {2012.02.23}
}

@ARTICLE{Antonini1992,
  author = {Antonini, M. and Barlaud, M. and Mathieu, P. and Daubechies, I.},
  title = {Image coding using wavelet transform},
  journal = {Image Processing, {IEEE} Transactions on},
  year = {1992},
  volume = {1},
  pages = {205--220},
  number = {2},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{aptoula2008alpha,
  author = {Aptoula, Erchan and Lef{\`e}vre, S{\'e}bastien},
  title = {$\alpha$-Trimmed lexicographical extrema for pseudo-morphological
	image analysis},
  journal = {Journal of Visual Communication and Image Representation},
  year = {2008},
  volume = {19},
  pages = {165--174},
  number = {3},
  __markedentry = {[Sagnik]},
  publisher = {Elsevier}
}

@ARTICLE{Atakishiyev1997,
  author = {Natig M. Atakishiyev and Kurt Bernardo Wolf},
  title = {Fractional Fourier--Kravchuk transform},
  journal = {J. Opt. Soc. Am. A},
  year = {1997},
  volume = {14},
  pages = {1467--1477},
  number = {7},
  month = {Jul},
  __markedentry = {[Sagnik]},
  abstract = {We introduce a model of multimodal waveguides with a finite number
	of sensor points. This is a finite oscillator whose eigenstates are
	Kravchuk functions, which are orthonormal on a finite set of points
	and satisfy a physically important difference equation. The fractional
	finite Fourier--Kravchuk transform is defined to self-reproduce these
	functions. The analysis of finite signal processing uses the representations
	of the ordinary rotation group SO(3). This leads naturally to a phase
	space for finite optics such that the continuum limit (N{\textrightarrow}$\infty$)
	reproduces Fourier paraxial optics.},
  doi = {10.1364/JOSAA.14.001467},
  owner = {Welcome},
  publisher = {OSA},
  timestamp = {2011.02.09},
  url = {http://josaa.osa.org/abstract.cfm?URI=josaa-14-7-1467}
}

@ARTICLE{Attias1999,
  author = {Attias, H.},
  title = {Independent factor analysis},
  journal = {Neural computation},
  year = {1999},
  volume = {11},
  pages = {803--851},
  number = {4},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@BOOK{B.E.A.Saleh1991,
  title = {Fundamentals of Photonics},
  publisher = {John Wiley and Sons Inc. USA},
  year = {1991},
  author = {B. E. A. Saleh, M. C. Teich},
  __markedentry = {[Sagnik]},
  owner = {Welcome},
  timestamp = {2011.02.13}
}

@ARTICLE{Bach2003,
  author = {Bach, {F.R.} and Jordan, {M.I.}},
  title = {Kernel independent component analysis},
  journal = {The Journal of Machine Learning Research},
  year = {2003},
  volume = {3},
  pages = {1--48},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{BACK1997,
  author = {{BACK}, {A.C.B.O.A.} and {AMARI}, S.},
  title = {{ON-LINE} {ADAPTIVE} {ALGORITHMS} {IN} {NON-STATIONARY} {ENVIRONMENTS}
	{USING} A {MODIFIED} {CONJUGATE} {GRADIENT} {APPROACH}},
  journal = {{NEURAL} {NETWORKS} {FOR} {SIGNAL} {PROCESSING} {VII}},
  year = {1997},
  pages = {316},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Barlow1981,
  author = {Barlow, H. B.},
  title = {The Ferrier Lecture, 1980: Critical Limiting Factors in the Design
	of the Eye and Visual Cortex},
  journal = {Proceedings of the Royal Society of London. Series B, Biological
	Sciences},
  year = {1981},
  volume = {212},
  pages = {1--34},
  number = {1186},
  month = may,
  note = {{ArticleType:} research-article / Full publication date: May 7, 1981
	/ Copyright \copyright{} 1981 The Royal Society},
  abstract = {The main factors limiting the performance of the peripheral parts
	of the visual system can be specified, and doing this clarifies the
	nature of the interpretive tasks that must be performed by the central
	parts of the system. It is argued that the critical factor that hinders
	development of better resolving power is the difficulty of confining
	light within the waveguide-like outer segment, and that for sensitivity
	this critical factor is the thermal decomposition of photosensitive
	pigments. Knowledge of these limits makes many surprising details
	of the eye intelligible. Understanding the difficulties posed by
	the narrow dynamic range of nerve fibres may give similar insight
	into the coding of the retinal image for transmission to the brain.
	Our level of understanding changes when we come to the visual cortex,
	for although we do not lack good anatomical and neurophysiological
	data, these do not make the principles of operation self-evident
	in the way that the structure of the eye immediately suggests that
	it is an image-forming device. The cortex converts the representation
	of the visual field that it receives into reliable knowledge of the
	world around us, and the trouble may be that we lack good models
	of how this can be done. A system that can respond to single quanta
	and resolve almost to the diffraction limit is unlikely to employ
	grossly inefficient methods for those higher functions upon which
	its whole utility depends, and so it is worth seeking out the limiting
	factors. The quality of human performance at certain higher perceptual
	tasks is high compared with the limit of reliable statistical inference;
	hence much of the sample of information available in a visual image
	must be effectively utilized. But there are strong limitations on
	the connectivity in the cortex, so that one is forced to consider
	how the relevant information can be collected together. Three stages
	of dealing with the visual image are proposed: the improvement of
	the cortical map in primary visual cortex by processes analogous
	to spatial and temporal interpolation; the detection of linking features
	in this map; and the concentration of this information by non-topographical
	mapping in adjacent visual areas.},
  issn = {0080-4649},
  owner = {Sagnik},
  shorttitle = {The Ferrier Lecture, 1980},
  timestamp = {2012.02.23},
  url = {http://www.jstor.org/stable/35490}
}

@ARTICLE{Barlow1989,
  author = {Barlow, {H.B.}},
  title = {Unsupervised learning},
  journal = {Neural computation},
  year = {1989},
  volume = {1},
  pages = {295--311},
  number = {3},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Bastiaans1985,
  author = {Bastiaans, M.},
  title = {On the sliding-window representation in digital signal processing},
  journal = {{IEEE} Transactions on Acoustics, Speech and Signal Processing},
  year = {1985},
  volume = {33},
  pages = {868-- 873},
  number = {4},
  month = aug,
  abstract = {The short-time Fourier transform of a discrete-time signal, which
	is the Fourier transform of a "windowed" version of the signal, is
	interpreted as a sliding-window spectrum. This sliding-window spectrum
	is a function of two variables: a discrete time index, which represents
	the position of the window, and a continuous frequency variable.
	It is shown that the signal can be reconstructed from the sampled
	sliding-window spectrum, i.e., from the values at the points of a
	certain time-frequency lattice. This sampling lattice is rectangular,
	and the rectangular cells occupy an area of 2\emph{[U+03C0]} in the
	time-frequency domain. It is shown that an elegant way to represent
	the signal directly in terms of the sample values of the sliding-window
	spectrum, is in the form of Gabor's signal representation. Therefore,
	a reciprocal window is introduced, and it is shown how the window
	and the reciprocal window are related. Gabor's signal representation
	then expands the signal in terms of properly shifted and modulated
	versions of the reciprocal window, and the expansion coefficients
	are just the values of the sampled sliding-window spectrum.},
  doi = {10.1109/TASSP.1985.1164653},
  issn = {0096-3518},
  keywords = {Digital signal processing, Fourier transforms, Lattices, Sampling
	methods, Signal analysis, Signal processing, Signal representations,
	Speech, Time frequency analysis},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Bastiaans1997,
  author = {Bastiaans, Martin J},
  title = {Application of the Wigner distribution function in optics},
  journal = {The Wigner Distribution Theory and Applications in Signal Processing},
  year = {1997},
  pages = {1--54},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Bastiaans1994,
  author = {Bastiaans, Martin J.},
  title = {Gabor?s signal expansion and the Zak transform},
  journal = {Applied Optics},
  year = {1994},
  volume = {33},
  pages = {5241--5255},
  number = {23},
  abstract = {Gabor's expansion of a signal into a discrete set of shifted and modulated
	versions of an elementary signal is introduced, and its relation
	to sampling of the sliding-window spectrum is shown. It is shown
	how Gabor's expansion coefficients can be found as samples of the
	sliding-window spectrum, in which the window function is related
	to the elementary signal in such a way that the set of shifted and
	modulated elementary signals is biorthonormal to the corresponding
	set of window functions. The Zak transform is introduced, and its
	intimate relationship to Gabor's signal expansion is demonstrated.
	It is shown how the Zak transform can be helpful in determining the
	window function that corresponds to a given elementary signal and
	how it can be used to find Gabor's expansion coefficients. The continuous-time
	and the discrete-time cases are considered, and, by sampling the
	continuous frequency variable that still occurs in the discrete-time
	case, the discrete Zak transform and the discrete Gabor transform
	are introduced. It is shown how the discrete transforms enable us
	to determine Gabor's expansion coefficients by a fast computer algorithm,
	which is analogous to the well-known fast Fourier-transform= algorithm.},
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	Conf},
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  volume = {5},
  pages = {3469--3472},
  __markedentry = {[Welcome][Sagnik]},
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  owner = {Welcome},
  timestamp = {2011.02.13}
}

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	their short-time Fourier transform},
  booktitle = {Proc. {ICA2000}},
  year = {2000},
  pages = {87--92},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

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  issn = {0165-1684},
  keywords = {Binary images},
  owner = {Sagnik},
  timestamp = {2011.05.25},
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	{IEEE} International Conference on},
  year = {2004},
  volume = {3},
  pages = {iii--889},
  owner = {Sagnik},
  shorttitle = {{TRINICON}},
  timestamp = {2012.02.23}
}

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@ARTICLE{Calhoun2004,
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  owner = {Sagnik},
  shorttitle = {Independent component analysis applied to {fMRI} data},
  timestamp = {2012.02.23}
}

@ARTICLE{Calhoun2004a,
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	analysis: application to visual, motor and visuomotor tasks},
  journal = {Magnetic resonance imaging},
  year = {2004},
  volume = {22},
  pages = {1181--1191},
  number = {9},
  owner = {Sagnik},
  shorttitle = {A method for comparing group {fMRI} data using independent component
	analysis},
  timestamp = {2012.02.23}
}

@ARTICLE{Calhoun2006,
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  year = {2006},
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  number = {2},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Calhoun2003,
  author = {Calhoun, {V.D.} and Adali, T. and Hansen, {L.K.} and Larsen, J. and
	Pekar, {J.J.}},
  title = {{ICA} of functional {MRI} data: an overview},
  booktitle = {in Proceedings of the International Workshop on Independent Component
	Analysis and Blind Signal Separation},
  year = {2003},
  owner = {Sagnik},
  shorttitle = {{ICA} of functional {MRI} data},
  timestamp = {2012.02.23}
}

@ARTICLE{Calhoun2002,
  author = {Calhoun, {VD} and Adal\i{}, T. and Pearlson, {GD} and Van Zijl, {PCM}
	and Pekar, {JJ}},
  title = {Independent component analysis of {fMRI} data in the complex domain},
  journal = {Magnetic Resonance in Medicine},
  year = {2002},
  volume = {48},
  pages = {180--192},
  number = {1},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Calhoun2001,
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  title = {A method for making group inferences from functional {MRI} data using
	independent component analysis},
  journal = {Human brain mapping},
  year = {2001},
  volume = {14},
  pages = {140--151},
  number = {3},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

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	Pekar, {JJ}},
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	time courses in a spatial {ICA} analysis},
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  year = {2005},
  volume = {25},
  pages = {527--538},
  number = {2},
  owner = {Sagnik},
  shorttitle = {Semi-blind {ICA} of {fMRI}},
  timestamp = {2012.02.23}
}

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  number = {3},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

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  pages = {562--571},
  number = {3},
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  author = {Cardoso, {J.F.}},
  title = {High-order contrasts for independent component analysis},
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  year = {1999},
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  number = {1},
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  timestamp = {2012.02.23}
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@ARTICLE{Cardoso1998,
  author = {Cardoso, {J.F.}},
  title = {Blind signal separation: statistical principles},
  journal = {Proceedings of the {IEEE}},
  year = {1998},
  volume = {86},
  pages = {2009--2025},
  number = {10},
  owner = {Sagnik},
  shorttitle = {Blind signal separation},
  timestamp = {2012.02.23}
}

@ARTICLE{Cardoso1997,
  author = {Cardoso, {J.F.}},
  title = {Infomax and maximum likelihood for blind source separation},
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  volume = {4},
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  number = {4},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Cardoso1992,
  author = {Cardoso, {J.F.}},
  title = {Iterative techniques for blind source separation using only fourth-order
	cumulants},
  booktitle = {Proc. {EUSIPCO}},
  year = {1992},
  volume = {92},
  pages = {739--742},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Cardoso1991,
  author = {Cardoso, {J.F.}},
  title = {Super-symmetric decomposition of the fourth-order cumulant tensor.
	Blind identification of more sources than sensors},
  booktitle = {Acoustics, Speech, and Signal Processing, 1991. {ICASSP-91.}, 1991
	International Conference on},
  year = {1991},
  pages = {3109--3112},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Cardoso1990,
  author = {Cardoso, {J.F.}},
  title = {Eigen-structure of the fourth-order cumulant tensor with application
	to the blind source separation problem},
  booktitle = {Acoustics, Speech, and Signal Processing, 1990. {ICASSP-90.}, 1990
	International Conference on},
  year = {1990},
  pages = {2655--2658},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

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  author = {Cardoso, {J.F.}},
  title = {Source separation using higher order moments},
  booktitle = {Acoustics, Speech, and Signal Processing, 1989. {ICASSP-89.}, 1989
	International Conference on},
  year = {1989},
  pages = {2109--2112},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Cardoso1996,
  author = {Cardoso, {J.F.} and Laheld, {B.H.}},
  title = {Equivariant adaptive source separation},
  journal = {Signal Processing, {IEEE} Transactions on},
  year = {1996},
  volume = {44},
  pages = {3017--3030},
  number = {12},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Cardoso2008,
  author = {Cardoso, {J.F.} and Le Jeune, M. and Delabrouille, J. and Betoule,
	M. and Patanchon, G.},
  title = {Component separation with flexible {models---Application} to multichannel
	astrophysical observations},
  journal = {{IEEE} Journal of Selected Topics in Signal Processing},
  year = {2008},
  volume = {2},
  pages = {735--746},
  number = {5},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Cardoso1993,
  author = {Cardoso, {J.F.} and Souloumiac, A.},
  title = {Blind beamforming for {non-Gaussian} signals},
  booktitle = {IEE Proceedings F, Radar and Signal Processing},
  year = {1993},
  volume = {140},
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  owner = {Sagnik},
  timestamp = {2012.02.23}
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@MISC{CenterforHistoryandNewMedia,
  author = {{{Center} for History and New Media}},
  title = {Zotero Quick Start Guide},
  howpublished = {http://zotero.org/support/quick\_start\_guide},
  annote = {Welcome to Zotero!
	
	View the Quick Start Guide to learn how to begin collecting, managing,
	citing, and sharing your research sources.
	
	Thanks for installing Zotero.},
  owner = {Sagnik},
  timestamp = {2012.02.23},
  url = {http://zotero.org/support/quick_start_guide}
}

@INPROCEEDINGS{Chan1996,
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  title = {Multi-channel signal separation},
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	Proceedings., 1996 {IEEE} International Conference on},
  year = {1996},
  volume = {2},
  pages = {649--652},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

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  author = {Chang, T. and Kuo, {C.C.J.}},
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  year = {1993},
  volume = {2},
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  number = {4},
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@ARTICLE{Chern2002,
  author = {Jyh-Long Chern and Ching-Chung Li and Sheng-Hui Tseng},
  title = {Blind phase retrieval and source separation of electromagnetic fields},
  journal = {Opt. Lett.},
  year = {2002},
  volume = {27},
  pages = {89--91},
  number = {2},
  month = {Jan},
  __markedentry = {[Sagnik]},
  abstract = {Blind source separation of two electromagnetic fields is investigated.
	The difficulty of this task lies in the fact that only the power,
	which is the square of the sum of the electromagnetic fields, can
	be directly measured; the cross term of the electromagnetic fields
	is inevitable, and a strong correlation occurs in blind deconvolution.
	However, the relative phase is physically different from the field
	intensities, and, hence, extracting the phase during separation seems
	inconceivable. Our results demonstrate that the intensities and the
	relative phase of two electromagnetic waves can be determined with
	eigenvalue problem formalism even when the mixing processes are completely
	unknown.},
  doi = {10.1364/OL.27.000089},
  keywords = {Continuous optical signal processing ; Phase; Waves},
  owner = {Welcome},
  publisher = {OSA},
  timestamp = {2011.02.09},
  url = {http://ol.osa.org/abstract.cfm?URI=ol-27-2-89}
}

@ARTICLE{Chi2002,
  author = {Chi, {C.Y.} and Chen, {C.H.} and Chen, {C.Y.}},
  title = {Blind {MAI} and {ISI} suppression for {DS/CDMA} systems using {HOS-based}
	inverse filter criteria},
  journal = {Signal Processing, {IEEE} Transactions on},
  year = {2002},
  volume = {50},
  pages = {1368--1381},
  number = {6},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Chi1995,
  author = {Chi, {C.Y.} and Wu, {M.C.}},
  title = {Inverse filter criteria for blind deconvolution and equalization
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  year = {1995},
  volume = {43},
  pages = {55--63},
  number = {1},
  owner = {Sagnik},
  timestamp = {2012.02.23}
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  author = {Choi, S. and Amari, S. and Cichocki, A. and Liu, R.},
  title = {Natural gradient learning with a nonholonomic constraint for blind
	deconvolution of multiple channels},
  booktitle = {First International Workshop on Independent Component Analysis and
	Signal Separation},
  year = {1999},
  pages = {371--376},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Choi2000,
  author = {Choi, S. and Cichocki, A.},
  title = {Blind separation of nonstationary and temporally correlated sources
	from noisy mixtures},
  booktitle = {Neural Networks for Signal Processing X, 2000. Proceedings of the
	2000 {IEEE} Signal Processing Society Workshop},
  year = {2000},
  volume = {1},
  pages = {405--414},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Choi2000a,
  author = {Choi, Seungjin and Cichocki, Andrzej},
  title = {Blind Separation of Nonstationary Sources in Noisy Mixtures},
  year = {2000},
  owner = {Sagnik},
  timestamp = {2012.02.23},
  url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.34.4931}
}

@ARTICLE{Choi2000c,
  author = {Choi, S. and Cichocki, A.},
  title = {Blind separation of nonstationary sources in noisy mixtures},
  journal = {Electronics Letters},
  year = {2000},
  volume = {36},
  pages = {848--849},
  number = {9},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Choi1997,
  author = {Choi, S. and Cichocki, A.},
  title = {Blind signal deconvolution by spatio-temporal decorrelation and demixing},
  booktitle = {Neural Networks for Signal Processing [1997] {VII.} Proceedings of
	the 1997 {IEEE} Workshop},
  year = {1997},
  pages = {426--435},
  keywords = {{Anti-Hebbian} learning, blind equalization, Blind equalizers, blind
	signal deconvolution, Blind source separation, Deconvolution, decorrelation,
	Delay, demixing, Filters, i.i.d. sources, inverse filter, local unsupervised
	learning algorithm, polynomial matrices, Signal processing algorithms,
	signal resolution, signal sources, Source separation, spatio-temporal
	decorrelation, Time domain analysis, two-stage neural network, Unsupervised
	learning, Vectors},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Choi2002,
  author = {Choi, S. and Cichocki, A. and Amari, S.},
  title = {Equivariant nonstationary source separation},
  journal = {Neural Networks},
  year = {2002},
  volume = {15},
  pages = {121--130},
  number = {1},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Choi2000b,
  author = {Choi, S. and Cichocki, A. and Amari, S.},
  title = {Local stability analysis of flexible independent component analysis
	algorithm},
  booktitle = {Acoustics, Speech, and Signal Processing, 2000. {ICASSP'00.} Proceedings.
	2000 {IEEE} International Conference on},
  year = {2000},
  volume = {6},
  pages = {3426--3429},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Choi2000d,
  author = {Choi, S. and Cichocki, A. and Amari, {S.I.}},
  title = {Flexible independent component analysis},
  journal = {The Journal of {VLSI} Signal Processing},
  year = {2000},
  volume = {26},
  pages = {25--38},
  number = {1},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Choi2002a,
  author = {Choi, S. and Cichocki, A. and Beloucharni, A.},
  title = {Second order nonstationary source separation},
  journal = {The Journal of {VLSI} Signal Processing},
  year = {2002},
  volume = {32},
  pages = {93--104},
  number = {1},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Choi2001,
  author = {Choi, S. and Cichocki, A. and Belouchrani, A.},
  title = {Blind separation of second-order nonstationary and temporally colored
	sources},
  booktitle = {Statistical Signal Processing, 2001. Proceedings of the 11th {IEEE}
	Signal Processing Workshop on},
  year = {2001},
  pages = {444--447},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Choudrey2001,
  author = {Choudrey, {R.A.} and Roberts, {S.J.}},
  title = {Flexible Bayesian independent component analysis for blind source
	separation},
  booktitle = {Proc. Int. Conf. on Independent Component Analysis and Signal Separation
	{(ICA2001)}},
  year = {2001},
  pages = {90--95},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@BOOK{Cichocki2002,
  title = {Blind Signal and Image Processing},
  publisher = {Wiley Online Library},
  year = {2002},
  author = {Cichocki, A. and Amari, S.},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Cichocki1998,
  author = {Cichocki, A. and Douglas, {SC} and Amari, S.},
  title = {Robust techniques for independent component analysis {(ICA)} with
	noisy data},
  journal = {Neurocomputing},
  year = {1998},
  volume = {22},
  pages = {113--130},
  number = {1},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Cichocki1996a,
  author = {Cichocki, A. and Kasprzak, W. and Amari, S. {-I}},
  title = {Adaptive Approach To Blind Source Separation With Cancellation Of
	Additive And Convolutional Noise},
  journal = {{IN} {INTERNATIONAL} {CONFERENCE} {ON} {SIGNAL} {PROCESSING}},
  year = {1996},
  pages = {412---415},
  owner = {Sagnik},
  timestamp = {2012.02.23},
  url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.48.9466}
}

@INPROCEEDINGS{Cichocki1997,
  author = {Cichocki, A. and Orsier, B. and Back, A. and Amari, {S.I.}},
  title = {On-line adaptive algorithms in non-stationary environments using
	a modified conjugate gradient approach},
  booktitle = {Neural Networks for Signal Processing [1997] {VII.} Proceedings of
	the 1997 {IEEE} Workshop},
  year = {1997},
  pages = {316--325},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Cichocki2000,
  author = {Cichocki, A. and Thawonmas, R.},
  title = {On-line algorithm for blind signal extraction of arbitrarily distributed,
	but temporally correlated sources using second order statistics},
  journal = {Neural Processing Letters},
  year = {2000},
  volume = {12},
  pages = {91--98},
  number = {1},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Cichocki1996,
  author = {Cichocki, A. and Unbehauen, R.},
  title = {Robust neural networks with on-line learning for blind identification
	and blind separation of sources},
  journal = {{IEEE} Transactions on Circuits and Systems I: Fundamental Theory
	and Applications},
  year = {1996},
  volume = {43},
  pages = {894--906},
  number = {11},
  month = nov,
  abstract = {Two unsupervised, self-normalizing, adaptive learning algorithms are
	developed for robust blind identification and/or blind separation
	of independent source signals from a linear mixture of them. One
	of these algorithms is developed for on-line learning of a single-layer
	feed-forward neural network model and a second one for a feedback
	(fully recurrent) neural network model. The proposed algorithms are
	robust, efficient, fast and suitable for real-time implementations.
	Moreover, they ensure the separation of extremely weak or badly scaled
	stationary signals, as well as a successful separation even if the
	mixture matrix is very ill-conditioned (near singular). The performance
	of the proposed algorithms is illustrated by computer simulation
	experiments},
  doi = {10.1109/81.542280},
  issn = {1057-7122},
  keywords = {Acoustic sensors, adaptive learning algorithms, adaptive signal processing,
	Biosensors, blind identification, blind separation, feedback neural
	network model, feedforward neural nets, Feedforward neural networks,
	fully recurrent neural network model, identification, independent
	source signals, Neural networks, Neurofeedback, online learning,
	real-time implementations, recurrent neural nets, Recurrent neural
	networks, robust neural networks, Robustness, Sensor arrays, Sensor
	phenomena and characterization, Signal processing, single-layer feedforward
	neural network model, Unsupervised learning, unsupervised self-normalizing
	learning algorithms},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Cichocki1994,
  author = {Cichocki, A. and Unbehauen, R. and Moszczynski, L. and Rummert, E.},
  title = {A new on-line adaptive learning algorithm for blind separation of
	source signals},
  booktitle = {Int. Symp. on Artificial Neural Networks},
  year = {1994},
  pages = {406--411},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Cichocki1994a,
  author = {Cichocki, A. and Unbehauen, R. and Rummert, E.},
  title = {Robust learning algorithm for blind separation of signals},
  journal = {Electronics letters},
  year = {1994},
  volume = {30},
  pages = {1386--1387},
  number = {17},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Cichocki2000a,
  author = {Cichocki, A. and Vorobyov, S.},
  title = {Application of {ICA} for automatic noise and interference cancellation
	in multisensory biomedical signals},
  booktitle = {Proceedings of the Second International Workshop on {ICA} and {BSS},
	{ICA}},
  year = {2000},
  pages = {621--626},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Cichocki1999,
  author = {Cichocki, A. and Zhang, L. and Rutkowski, T.},
  title = {Blind separation and filtering using state space models},
  booktitle = {Circuits and Systems, 1999. {ISCAS'99.} Proceedings of the 1999 {IEEE}
	International Symposium on},
  year = {1999},
  volume = {5},
  pages = {78--81},
  keywords = {adaptive signal processing, Biomedical signal processing, biomedical
	signals, Blind equalizers, blind filtering, blind separation, Brain
	modeling, Deconvolution, {ECG}, {EEG}, Electroencephalography, {EMG},
	{EOG}, Filtering, filtering theory, Geophysical signal processing,
	Independent component analysis, medical signal processing, {MEG},
	multichannel blind deconvolution, mutual independence, nonlinear
	mixture hyper radial basis function, output signals, signal detection,
	Signal processing, source localization, speech enhancement, speech
	processing, state space models, State-space methods, supervised-unsupervised
	learning rules, unsupervised adaptive learning algorithms, wireless
	communications},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Cincotti1992,
  author = {Cincotti, G and Gori, F and Santarsiero, M},
  title = {Generalized {self-Fourier} functions},
  journal = {Journal of Physics A: Mathematical and General},
  year = {1992},
  volume = {25},
  pages = {L1191--L1194},
  number = {20},
  month = oct,
  doi = {10.1088/0305-4470/25/20/001},
  issn = {0305-4470, 1361-6447},
  owner = {Sagnik},
  timestamp = {2012.02.23},
  url = {http://iopscience.iop.org/0305-4470/25/20/001}
}

@ARTICLE{Coffey1994,
  author = {Coffey, Mark W.},
  title = {Self-reciprocal Fourier functions},
  journal = {Journal of the Optical Society of America A},
  year = {1994},
  volume = {11},
  pages = {2453--2455},
  number = {9},
  abstract = {By definition, a self-reciprocal {(SR)} function is its own Fourier
	or Hankel transform. Areas of application of {SR} functions, including
	Fourier optics, are noted. Integral representations for {SR} functions
	are obtained and are illustrated with the exponential Fourier transformation
	on the half-line. It is pointed out that there are a large number
	of classes of {SR} functions, and examples of these functions are
	given.},
  doi = {10.1364/JOSAA.11.002453},
  owner = {Sagnik},
  timestamp = {2012.02.23},
  url = {http://josaa.osa.org/abstract.cfm?URI=josaa-11-9-2453}
}

@BOOK{Cohen1995,
  title = {Time-frequency analysis},
  publisher = {Prentice Hall {PTR}},
  year = {1995},
  author = {Cohen, L\'eon},
  abstract = {Featuring traditional coverage as well as new research results that,
	until now, have been scattered throughout the professional literature,
	this book brings togetherin simple languagethe basic ideas and methods
	that have been developed to study natural and man-made signals whose
	frequency content changes with timee.g., speech, sonar and radar,
	optical images, mechanical vibrations, acoustic signals, biological/biomedical
	and geophysical {signals.Covers} time analysis, frequency analysis,
	and scale analysis; time-bandwidth relations; instantaneous frequency;
	densities and local quantities; the short time Fourier Transform;
	time-frequency analysis; the Wigner representation; time-frequency
	representations; computation methods; the synthesis problem; spatial-spatial/frequency
	representations; time-scale representations; operators; general joint
	representations; stochastic signals; and higher order time-frequency
	distributions. Illustrates each concept with examples and shows how
	the methods have been extended to other variables, such as {scale.For}
	engineers, acoustic scientists, medical scientists and developers,
	mathematicians, physicists, and mangers working in the fields of
	acoustics, sonar, radar, image processing, biomedical devices, communication.},
  isbn = {9780135945322},
  keywords = {Frequency spectra, Mathematics / Probability \& Statistics / General,
	Signal processing, Technology \& Engineering / Electrical, Technology
	\& Engineering / Engineering {(General)}, Technology \& Engineering
	/ Telecommunications, Time-series analysis},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Cohen1989,
  author = {Cohen, L.},
  title = {Time-frequency distributions-a review},
  journal = {Proceedings of the {IEEE}},
  year = {1989},
  volume = {77},
  pages = {941--981},
  number = {7},
  month = jul,
  abstract = {A review and tutorial of the fundamental ideas and methods of joint
	time-frequency distributions is presented. The objective of the field
	is to describe how the spectral content of a signal changes in time
	and to develop the physical and mathematical ideas needed to understand
	what a time-varying spectrum is. The basic gal is to devise a distribution
	that represents the energy or intensity of a signal simultaneously
	in time and frequency. Although the basic notions have been developing
	steadily over the last 40 years, there have recently been significant
	advances. This review is intended to be understandable to the nonspecialist
	with emphasis on the diversity of concepts and motivations that have
	gone into the formation of the field},
  doi = {10.1109/5.30749},
  issn = {0018-9219},
  keywords = {Astronomy, Cities and towns, diversity of concepts, Fourier transforms,
	fundamental ideas, joint time-frequency distributions, motivations,
	Physics, review, reviews, Signal analysis, Signal processing, signal
	resolution, spectral analysis, Spectrogram, Speech analysis, Strips,
	Time frequency analysis, time-varying spectrum, tutorial},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Comon1994,
  author = {Comon, P.},
  title = {Independent component analysis, a new concept?},
  journal = {Signal processing},
  year = {1994},
  volume = {36},
  pages = {287--314},
  number = {3},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{cong2003historical,
  author = {Cong, J.X.},
  title = {Historical Development of Central Limit Theorem (CLT)},
  year = {2003},
  organization = {Technical report, Rice University, Houston, TX, February 2003. Dispon{\'\i}vel
	on-line em http://www. stat. rice. edu/~ blairc/seminar/Files/julieTalk.
	pdf}
}

@ARTICLE{Correa2007,
  author = {Correa, N. and Adali, T. and Calhoun, {V.D.}},
  title = {Performance of blind source separation algorithms for {fMRI} analysis
	using a group {ICA} method},
  journal = {Magnetic resonance imaging},
  year = {2007},
  volume = {25},
  pages = {684--694},
  number = {5},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Courcelle1999,
  author = {Courcelle, Bruno and Olive, Fr\'ed\'eric},
  title = {Une axiomatisation au premier ordre des arrangements de pseudodroites
	euclidiennes},
  year = {1999},
  volume = {49},
  pages = {883--904},
  number = {3},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@BOOK{cover1991elements,
  title = {Elements of information theory},
  publisher = {Wiley Online Library},
  year = {1991},
  author = {Cover, T.M. and Thomas, J.A. and Wiley, J. and others},
  volume = {6}
}

@ARTICLE{cruces2004blind,
  author = {Cruces-Alvarez, S.A. and Cichocki, A. and Amari, S.},
  title = {From blind signal extraction to blind instantaneous signal separation:
	criteria, algorithms, and stability},
  journal = {IEEE Transactions on Neural Networks},
  year = {2004},
  volume = {15},
  pages = {859--873},
  number = {4},
  publisher = {IEEE}
}

@ARTICLE{D1995,
  author = {D, Choudhury and {P.N}, Puntambekar and {A.K}, Chakraborty},
  title = {Optical synthesis of {self-Fourier} functions},
  journal = {Optics Communications},
  year = {1995},
  volume = {119},
  pages = {279--282},
  number = {3},
  doi = {10.1016/0030-4018(95)00373-G},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Dale-Jones1993,
  author = {R Dale-Jones and T Tjahjadi},
  title = {A study and modification of the local histogram equalization algorithm},
  journal = {Pattern Recognition},
  year = {1993},
  volume = {26},
  pages = {1373 - 1381},
  number = {9},
  __markedentry = {[Sagnik]},
  doi = {DOI: 10.1016/0031-3203(93)90143-K},
  issn = {0031-3203},
  keywords = {Contrast enhancement},
  owner = {Sagnik},
  timestamp = {2011.05.25},
  url = {http://www.sciencedirect.com/science/article/pii/003132039390143K}
}

@BOOK{Daubechies1992,
  title = {Ten lectures on wavelets},
  publisher = {{SIAM}},
  year = {1992},
  author = {Daubechies, Ingrid},
  month = jun,
  abstract = {This monograph contains 10 lectures presented by Dr. Daubechies as
	the principal speaker at the 1990 {CBMS-NSF} Conference on Wavelets
	and Applications. Wavelets are a mathematical development that many
	experts think may revolutionize the world of information storage
	and retrieval. They are a fairly simple mathematical tool now being
	applied to the compression of data, such as fingerprints, weather
	satellite photographs, and medical x-rays - that were previously
	thought to be impossible to condense without losing crucial details.
	The opening chapter provides an overview of the main problems presented
	in the book. Following chapters discuss the theoretical and practical
	aspects of wavelet theory, including wavelet transforms, orthonormal
	bases of wavelets, and characterization of functional spaces by means
	of wavelets. The last chapter presents several topics under active
	research, as multidimensional wavelets, wavelet packet bases, and
	a construction of wavelets tailored to decompose functions defined
	in a finite interval.},
  isbn = {9780898712742},
  keywords = {Congresses, Mathematics, Mathematics / Applied, Mathematics / Differential
	Equations, Mathematics / General, Mathematics / Mathematical Analysis,
	Mathematics / Probability \& Statistics / General, Ondelettes, Science
	/ Waves \& Wave Mechanics, Technology \& Engineering / General, Wavelets
	{(Mathematics)}, Wavelets {(Mathematics)/} Congresses},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Daubechies1990,
  author = {Daubechies, I.},
  title = {The wavelet transform, time-frequency localization and signal analysis},
  journal = {Information Theory, {IEEE} Transactions on},
  year = {1990},
  volume = {36},
  pages = {961--1005},
  number = {5},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@BOOK{DeLathauwer1997,
  title = {Signal processing based on multilinear algebra},
  publisher = {Katholieke Universiteit Leuven},
  year = {1997},
  author = {De Lathauwer, L.},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{DeLathauwer1998,
  author = {De Lathauwer, L. and De Moor, B.},
  title = {From matrix to tensor: Multilinear algebra and signal processing},
  booktitle = {{INSTITUTE} {OF} {MATHEMATICS} {AND} {ITS} {APPLICATIONS} {CONFERENCE}
	{SERIES}},
  year = {1998},
  volume = {67},
  pages = {1--16},
  owner = {Sagnik},
  shorttitle = {From matrix to tensor},
  timestamp = {2012.02.23}
}

@ARTICLE{DeLathauwer2000,
  author = {De Lathauwer, L. and De Moor, B. and Vandewalle, J.},
  title = {A multilinear singular value decomposition},
  journal = {{SIAM} Journal on Matrix Analysis and Applications},
  year = {2000},
  volume = {21},
  pages = {1253--1278},
  number = {4},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{DeLathauwer2000a,
  author = {De Lathauwer, L. and De Moor, B. and Vandewalle, J.},
  title = {Fetal electrocardiogram extraction by blind source subspace separation},
  journal = {Biomedical Engineering, {IEEE} Transactions on},
  year = {2000},
  volume = {47},
  pages = {567--572},
  number = {5},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{DeLathauwer1996,
  author = {De Lathauwer, L. and De Moor, B. and Vandewalle, J.},
  title = {Independent component analysis based on higher-order statistics only},
  booktitle = {In Proceedings of 8th {IEEE} Signal Processing Workshop on Statistical
	Signal and Array Processing},
  year = {1996},
  pages = {356--359},
  keywords = {additive Gaussian noise, Additive noise, algorithms, Blind source
	separation, canonical decomposition, congruence transformation, correlation
	methods, data decorrelation, decorrelation, Gaussian noise, Givens
	type iteration, higher order only technique, Higher order statistics,
	higher-order cumulant tensor, identification, identification problem,
	Independent component analysis, Information processing, iterative
	methods, Jacobian matrices, linear algebra, matrix algebra, Matrix
	decomposition, matrix diagonalization, multilinear algebra, prewhitening,
	Signal processing, simultaneous Schur decomposition, statistical
	analysis, Tensile stress, white noise},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{DeLathauwer2004,
  author = {De Lathauwer, L. and Vandewalle, J.},
  title = {Dimensionality reduction in higher-order signal processing and {rank-(R1},
	R2,..., {RN)} reduction in multilinear algebra},
  journal = {Linear Algebra and its Applications},
  year = {2004},
  volume = {391},
  pages = {31--55},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{DECORRELATION,
  author = {{DECORRELATION}, {S.T.}},
  title = {Seungjin {CHOI} and Andrzej {CICHOCKI} Lab for Artificial Brain Systems
	Frontier Research Program, {RIKEN} 2-1 Hirosawa, Wako-shi Saitama
	351-01, Japan},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@BOOK{DeGroot2001,
  title = {Probability and Statistics-International Edition},
  publisher = {Addison-Wesley. Publishing. Company., Reading, Massachusetts},
  year = {2001},
  author = {DeGroot, MH and Schervish, MJ}
}

@BOOK{degroot1986probability,
  title = {Probability and statistics},
  publisher = {Addison-Wesley Reading, MA},
  year = {1986},
  author = {DeGroot, M.H. and Schervish, M.J. and Fang, X. and Lu, L. and Li,
	D.},
  volume = {2}
}

@ARTICLE{Delorme2004,
  author = {Delorme, A. and Makeig, S.},
  title = {{EEGLAB:} an open source toolbox for analysis of single-trial {EEG}
	dynamics including independent component analysis},
  journal = {Journal of neuroscience methods},
  year = {2004},
  volume = {134},
  pages = {9--21},
  number = {1},
  owner = {Sagnik},
  shorttitle = {{EEGLAB}},
  timestamp = {2012.02.23}
}

@ARTICLE{Delorme2007,
  author = {Delorme, A. and Sejnowski, T. and Makeig, S.},
  title = {Enhanced detection of artifacts in {EEG} data using higher-order
	statistics and independent component analysis},
  journal = {Neuroimage},
  year = {2007},
  volume = {34},
  pages = {1443--1449},
  number = {4},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@BOOK{Ding2001,
  title = {Blind equalization and identification},
  publisher = {Marcel Dekker},
  year = {2001},
  author = {Ding, Zhi and Li, Geoffrey},
  month = jan,
  abstract = {This text seeks to clarify various contradictory claims regarding
	capabilities and limitations of blind equalization. It highlights
	basic operating conditions and potential for malfunction. The authors
	also address concepts and principles of blind algorithms for single
	input multiple output {(SIMO)} systems and multi-user extensions
	of {SIMO} equalization and identification.},
  isbn = {9780824704797},
  keywords = {Digital communications, Medical / General, Signal processing, Signal
	processing - Digital techniques, Signal processing/ Digital techniques,
	Technology \& Engineering / Electrical, Technology \& Engineering
	/ Electronics / Digital, Technology \& Engineering / Engineering
	{(General)}, Technology \& Engineering / Telecommunications},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Djinovic2010,
  author = {Z. Djinovic and M. Tomic and C. Gamauf},
  title = {Fiber-optic interferometric sensor of magnetic field for structural
	health monitoring},
  journal = {Procedia Engineering},
  year = {2010},
  volume = {5},
  pages = {1103 - 1106},
  note = {Eurosensor XXIV Conference, Eurosensor XXIV Conference},
  __markedentry = {[Sagnik]},
  doi = {DOI: 10.1016/j.proeng.2010.09.303},
  issn = {1877-7058},
  keywords = {Fiber-optic sensors},
  owner = {Sagnik},
  timestamp = {2011.03.03},
  url = {http://www.sciencedirect.com/science/article/B9869-519FG5Y-9N/2/71831e0c8d8ffa2762b6a2f371ddc20a}
}

@ARTICLE{Dobrea,
  author = {Dobrea, {D.M.} and Dobrea, {M.C.}},
  title = {An Application of a Neuronal Method Used to Remove Artefacts},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Dong1997,
  author = {Bi-Zhen Dong and Yan Zhang and Ben-Yuan Gu and Guo-Zhen Yang},
  title = {Numerical investigation of phase retrieval in a fractional Fourier
	transform},
  journal = {J. Opt. Soc. Am. A},
  year = {1997},
  volume = {14},
  pages = {2709--2714},
  number = {10},
  month = {Oct},
  __markedentry = {[Sagnik]},
  abstract = {Recently the combination of the Gerchberg--Saxton (GS) algorithm anda
	fractional Fourier transform was proposed to implement beam shaping
	in thefractional Fourier domain \[Zalevsky et al., Opt. Lett. 21,
	842 (1996)\]. We generalize this idea to deal with the problem of
	phase retrievalfrom two intensity measurements in a fractional Fourier
	transform system.The relevant equations for determining the unknown
	phases are derived, basedon the general theory of amplitude--phase
	retrieval in an optical system.The unitarity condition of the fractional
	Fourier transform in a practicaloptical system with finite aperture
	is discussed. For different fractionalorders P, the phase retrieval
	of several typical modelimages is studied in detail. A comparison
	of the GS and our algorithms isgiven, based on numerical simulations.
	It follows that our algorithm can offerthe desired phase in all cases
	considered. However, the GS algorithm may failwhen the transform
	system is nonunitary.},
  doi = {10.1364/JOSAA.14.002709},
  owner = {Welcome},
  publisher = {OSA},
  timestamp = {2011.02.09},
  url = {http://josaa.osa.org/abstract.cfm?URI=josaa-14-10-2709}
}

@ARTICLE{Donoho1995,
  author = {Donoho, D. L., \& Johnstone, I. M.},
  title = {De-noising by soft-thresholding},
  journal = {IEEE Transaction on Information Theory},
  year = {1995},
  volume = {41},
  pages = {613-627},
  __markedentry = {[Sagnik]},
  owner = {Sagnik},
  timestamp = {2011.05.02}
}

@BOOK{Dorf1998,
  title = {Modern Control Systems: Solutions Manual},
  publisher = {{Addison-Wesley}},
  year = {1998},
  author = {Dorf, {R.C.} and Bishop, {R.H.}},
  owner = {Sagnik},
  shorttitle = {Modern Control Systems},
  timestamp = {2012.02.23}
}

@ARTICLE{Dorsch1994,
  author = {Dorsch, {R.G.} and Lohmann, {A.W.} and Bitran, Y. and Mendlovic,
	D. and Ozaktas, {H.M.}},
  title = {Chirp filtering in the fractional Fourier domain},
  journal = {Applied optics},
  year = {1994},
  volume = {33},
  pages = {7599--7602},
  number = {32},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Douglas2003,
  author = {Douglas, Scott C. and Sun, Xiaoan},
  title = {Convolutive blind separation of speech mixtures using the natural
	gradient},
  journal = {Speech Commun.},
  year = {2003},
  volume = {39},
  pages = {65--78},
  number = {1-2},
  month = jan,
  doi = {10.1016/S0167-6393(02)00059-6},
  issn = {0167-6393},
  owner = {Sagnik},
  timestamp = {2012.02.23},
  url = {http://dl.acm.org/citation.cfm?id=781587.781593}
}

@INPROCEEDINGS{Douglas1997,
  author = {Douglas, {S.C.} and Haykin, S.},
  title = {On the relationship between blind deconvolution and blind source
	separation},
  booktitle = {Signals, Systems \& Computers, 1997. Conference Record of the {Thirty-First}
	Asilomar Conference on},
  year = {1997},
  volume = {2},
  pages = {1591--1595},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Douglas2005,
  author = {Douglas, {S.C.} and Sawada, H. and Makino, S.},
  title = {Natural gradient multichannel blind deconvolution and speech separation
	using causal {FIR} filters},
  journal = {{IEEE} Transactions on Speech and Audio Processing},
  year = {2005},
  volume = {13},
  pages = {92--104},
  number = {1},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Dragoman1997,
  author = {Dragoman},
  title = {I: The Wigner Distribution Function in Optics and Optoelectronics},
  journal = {Progress in Optics},
  year = {1997},
  volume = {37},
  pages = {1--56},
  owner = {Sagnik},
  shorttitle = {I},
  timestamp = {2012.02.23}
}

@ARTICLE{Dragoman1996,
  author = {Dragoman},
  title = {Wigner distribution function in nonlinear optics.},
  journal = {Applied Optics},
  year = {1996},
  volume = {35},
  pages = {4142--4146},
  number = {21},
  doi = {10.1364/AO.35.004142},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Duarte2006,
  author = {Duarte, L. and Suyama, R. and de Faissol Attux, R. and Von Zuben,
	F. and Romano, J.},
  title = {Blind source separation of post-nonlinear mixtures using evolutionary
	computation and order statistics},
  journal = {Independent Component Analysis and Blind Signal Separation},
  year = {2006},
  pages = {66--73},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@BOOK{Dudgeon1983,
  title = {Multidimensional Digital Signal Processing},
  publisher = {Prentice Hall},
  year = {1983},
  author = {Dudgeon, Dan E. and Mersereau, Russell M.},
  month = sep,
  isbn = {0136049591},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Dyrholm2007,
  author = {Dyrholm, M. and Makeig, S. and Hansen, {L.K.}},
  title = {Model selection for convolutive {ICA} with an application to spatiotemporal
	analysis of {EEG}},
  journal = {Neural Computation},
  year = {2007},
  volume = {19},
  pages = {934--955},
  number = {4},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Ehlers1997,
  author = {Ehlers, F. and Schuster, {HG}},
  title = {Blind separation of convolutive mixtures and an application in automatic
	speech recognition in a noisy environment},
  journal = {Signal Processing, {IEEE} Transactions on},
  year = {1997},
  volume = {45},
  pages = {2608--2612},
  number = {10},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Engheta1996,
  author = {Engheta, N.},
  title = {On fractional calculus and fractional multipoles in electromagnetism},
  journal = {{IEEE} Transactions on Antennas and Propagation},
  year = {1996},
  volume = {44},
  pages = {554--566},
  number = {4},
  month = apr,
  abstract = {Using the concept and tools of fractional calculus, we introduce a
	definition for ``fractional-order'' multipoles of electric-charge
	densities, and we show that as far as their scalar potential distributions
	are concerned, such fractional-order multipoles effectively behave
	as ``intermediate'' sources bridging the gap between the cases of
	integer-order point multipoles such as point monopoles, point dipoles,
	point quadrupoles, etc. This technique, which involves fractional
	differentiation or integration of the Dirac delta function, provides
	a tool for formulating an electric source distribution whose potential
	functions can be obtained by using fractional differentiation or
	integration of potentials of integer-order point-multipoles of lower
	or higher orders. As illustrative examples, the cases of three-dimensional
	(point source) and two-dimensional (line source) problems in electrostatics
	are treated in detail, and an extension to the time-harmonic case
	is also addressed. In the three-dimensional electrostatic example,
	we suggest an electric-charge distribution which can be regarded
	as an ``intermediate'' case between cases of the electric-point monopole
	(point charge) and the electric-point dipole (point dipole), and
	we present its electrostatic potential which behaves as {r-(1+\emph{[U+03B1]})P\emph{[U+03B1]}(-cos\emph{[U+03B8]})}
	where 0{\textbackslash}textless\emph{[U+03B1]}{\textbackslash}textless1
	and P\emph{[U+03B1]}(\textperiodcentered{}) is the Legendre function
	of noninteger degree \emph{[U+03B1]}, thus denoting this charge distribution
	as a fractional 2\emph{[U+03B1]}-pole. At the two limiting cases
	of \emph{[U+03B1]}=0 and \emph{[U+03B1]}=1, this fractional 2\emph{[U+03B1]}
	-pole becomes the standard point monopole and point dipole, respectively.
	A corresponding intermediate fractional-order multipole is also given
	for the two-dimensional electrostatic case. Potential applications
	of this treatment to the image method in electrostatic problems are
	briefly mentioned. Physical insights and interpretation for such
	fractional-order 2\emph{[U+03B1]}-poles are also given},
  doi = {10.1109/8.489308},
  issn = {{0018-926X}},
  keywords = {2d problems, {3D} problems, Bibliographies, current density, Differential
	equations, differentiation, Dirac delta function, Educational institutions,
	electric charge densities, electric point dipoles, electric potential,
	electric source distribution, Electrodynamics, Electromagnetic propagation,
	electromagnetism, electrostatic potential, electrostatic problems,
	Electrostatics, Fractals, Fractional calculus, fractional differentiation,
	fractional integration, fractional multipoles, fractional order multipoles,
	History, image method, integer order point multipoles, integration,
	intermediate sources, Legendre function, Mathematics, point charge,
	point monopoles, point quadrupoles, potential functions, scalar potential
	distributions},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Engheta1996a,
  author = {Engheta, N.},
  title = {Electrostatic ``fractional'' image methods for perfectly conducting
	wedges and cones},
  journal = {{IEEE} Transactions on Antennas and Propagation},
  year = {1996},
  volume = {44},
  pages = {1565--1574},
  number = {12},
  month = dec,
  abstract = {Engheta (1996) introduced a definition for the electric charge ``fractional-order''
	multipoles using the concept of fractional derivatives and integrals.
	Here, we utilize that definition to introduce a detailed image theory
	for the two-dimensional {(2-D)} electrostatic potential distributions
	in front of a perfectly conducting wedge with arbitrary wedge angles,
	and for the three-dimensional potential in front of a perfectly conducting
	cone with arbitrary cone angles. We show that the potentials in the
	presence of these structures can be described equivalently as the
	electrostatic potentials of sets of equivalent ``image'' charge distributions
	that effectively behave as ``fractional-order'' multipoles; hence,
	the name ``fractional'' image methods. The fractional orders of these
	so-called fractional images depend on the wedge angle (for the wedge
	problem) and on the cone angle (for the cone problem). Special cases
	where these fractional images behave like the discrete images are
	discussed, and physical justification and insights into these results
	are given},
  doi = {10.1109/8.546242},
  issn = {{0018-926X}},
  keywords = {cone angle, Dielectrics, electric charge, electric charge fractional-order
	multipoles, electric potential, Electromagnetic fields, electrostatic
	fractional image methods, Electrostatics, equivalent image charge
	distributions, Fractional calculus, fractional images, Geometry,
	image theory, Kelvin, Laplace equations, Material properties, perfectly
	conducting cones, perfectly conducting wedges, three-dimensional
	potential, Two dimensional displays, two-dimensional electrostatic
	potential distributions, wedge angle},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Eriksson2002,
  author = {Eriksson, J. and Koivunen, V.},
  title = {Blind identifiability of class of nonlinear instantaneous {ICA} models},
  booktitle = {Proc. of the {XI} European Signal Proc. {Conf.(EUSIPCO} 2002},
  year = {2002},
  volume = {2},
  pages = {7--10},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Esposito2005,
  author = {Esposito, F. and Scarabino, T. and Hyvarinen, A. and Himberg, J.
	and Formisano, E. and Comani, S. and Tedeschi, G. and Goebel, R.
	and Seifritz, E. and Di Salle, F.},
  title = {Independent component analysis of {fMRI} group studies by self-organizing
	clustering},
  journal = {Neuroimage},
  year = {2005},
  volume = {25},
  pages = {193--205},
  number = {1},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Esposito2003,
  author = {Esposito, F. and Seifritz, E. and Formisano, E. and Morrone, R. and
	Scarabino, T. and Tedeschi, G. and Cirillo, S. and Goebel, R. and
	Di Salle, F.},
  title = {Real-time independent component analysis of {fMRI} time-series},
  journal = {{NeuroImage}},
  year = {2003},
  volume = {20},
  pages = {2209--2224},
  number = {4},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Everson1999,
  author = {Everson, R. and Roberts, S.},
  title = {Independent component analysis: A flexible nonlinearity and decorrelating
	manifold approach},
  journal = {Neural computation},
  year = {1999},
  volume = {11},
  pages = {1957--1983},
  number = {8},
  owner = {Sagnik},
  shorttitle = {Independent component analysis},
  timestamp = {2012.02.23}
}

@ARTICLE{Fan2011,
  author = {Chun-Nian Fan and Fu-Yan Zhang},
  title = {Homomorphic filtering based illumination normalization method for
	face recognition},
  journal = {Pattern Recognition Letters},
  year = {2011},
  volume = {32},
  pages = {1468 - 1479},
  number = {10},
  __markedentry = {[Sagnik]},
  doi = {DOI: 10.1016/j.patrec.2011.03.023},
  issn = {0167-8655},
  keywords = {Face recognition},
  owner = {Sagnik},
  timestamp = {2011.05.25},
  url = {http://www.sciencedirect.com/science/article/pii/S0167865511001000}
}

@INPROCEEDINGS{Farah2003,
  author = {Farah, {IR} and Ahmed, {M.B.} and Boussema, {MR}},
  title = {Multispectral satellite image analysis based on the method of blind
	separation and fusion of sources},
  booktitle = {Geoscience and Remote Sensing Symposium, 2003. {IGARSS'03.} Proceedings.
	2003 {IEEE} International},
  year = {2003},
  volume = {6},
  pages = {3638--3640},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Farah2002,
  author = {Farah, {IR} and Ahmed, {MB}},
  title = {Satellite image analysis based on the method of blind separation
	of sources for the extraction of information},
  booktitle = {Geoscience and Remote Sensing Symposium, 2002. {IGARSS'02.} 2002
	{IEEE} International},
  year = {2002},
  volume = {2},
  pages = {919--921},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Farina2004,
  author = {Farina, D. and F\'evotte, C. and Doncarli, C. and Merletti, R.},
  title = {Blind separation of linear instantaneous mixtures of nonstationary
	surface myoelectric signals},
  journal = {Biomedical Engineering, {IEEE} Transactions on},
  year = {2004},
  volume = {51},
  pages = {1555--1567},
  number = {9},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Feichtinger1992,
  author = {Feichtinger, {H.G.} and Gr\"ochenig, K.},
  title = {Gabor wavelets and the Heisenberg group: Gabor expansions and short
	time Fourier transform from the group theoretical point of view},
  year = {1992},
  owner = {Sagnik},
  shorttitle = {Gabor wavelets and the Heisenberg group},
  timestamp = {2012.02.23}
}

@ARTICLE{Funaro2003,
  author = {Funaro, M. and Oja, E. and Valpola, H.},
  title = {Independent component analysis for artefact separation in astrophysical
	images},
  journal = {Neural networks},
  year = {2003},
  volume = {16},
  pages = {469--478},
  number = {3-4},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Gandini2011,
  author = {M. Gandini and F. Lombardi and F. Vaccarino},
  title = {Blind separation of manufacturing variability with Independent Component
	Analysis: a convolutive approach},
  journal = {Expert Systems with Applications},
  year = {2011},
  volume = {In Press, Accepted Manuscript},
  pages = { - },
  __markedentry = {[Sagnik]},
  doi = {DOI: 10.1016/j.eswa.2011.02.036},
  issn = {0957-4174},
  keywords = {Independent component analysis},
  owner = {Sagnik},
  timestamp = {2011.02.21},
  url = {http://www.sciencedirect.com/science/article/B6V03-5259C36-5/2/35711ec0b7ac34e736b2429fa405aca1}
}

@PHDTHESIS{Gao2011,
  author = {B. Gao},
  title = {Single Channel Blind Source Separation},
  school = {Newcastle University},
  year = {2011},
  address = {School of Elctrical, Electronic and Computer Engineering},
  owner = {Sagnik},
  timestamp = {2013.03.09},
  url = {https://theses.ncl.ac.uk/dspace/bitstream/10443/1300/1/Gao11.pdf}
}

@ARTICLE{Gardner1991,
  author = {Gardner, W. A},
  title = {A new method of channel identification},
  journal = {{IEEE} Transactions on Communications},
  year = {1991},
  volume = {39},
  pages = {813--817},
  number = {6},
  month = jun,
  abstract = {A method of channel identification is proposed that exploits the spectral
	correlation properties of pulse- and carrier-modulated signals to
	identify channels in the presence of arbitrary noise and nearly arbitrary
	interference. Although a pilot or training signal is required, no
	replica of the transmitted pilot/training signal is needed at the
	receiver. The price paid for this simplicity and the tolerance to
	extreme channel corruption from noise or interference is that the
	method is slow. That is, relatively long averaging times are needed
	for measurement of the spectral correlation of the received signal},
  doi = {10.1109/26.87168},
  issn = {0090-6778},
  keywords = {Adaptive equalizers, averaging times, carrier-modulated signals, channel
	corruption, channel identification, Data communication, Digital modulation,
	Distortion measurement, Interference, noise, pilot signal, pulse
	modulated signals, Pulse modulation, Pulse shaping methods, received
	signal, Shape, Signal processing, spectral analysis, spectral correlation
	measurement, spectral correlation properties, telecommunication channels,
	training signal, Transfer functions},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Gedamu2010,
  author = {Pierrick Coup\emph{[U+9821]}nd Jos\emph{[U+9816]}. Manj\emph{[U+000EE821]}nd
	Elias Gedamu and Douglas Arnold and Montserrat Robles and D. Louis
	Collins},
  title = {Robust Rician noise estimation for MR images},
  journal = {Medical Image Analysis},
  year = {2010},
  volume = {14},
  pages = {483 - 493},
  number = {4},
  __markedentry = {[Sagnik]},
  doi = {DOI: 10.1016/j.media.2010.03.001},
  issn = {1361-8415},
  keywords = {Rician noise},
  owner = {Sagnik},
  timestamp = {2011.05.25},
  url = {http://www.sciencedirect.com/science/article/pii/S1361841510000241}
}

@ARTICLE{Gelle2000,
  author = {Gelle, G. and Colas, M. and Delaunay, G.},
  title = {Blind sources separation applied to rotating machines monitoring
	by acoustical and vibrations analysis},
  journal = {Mechanical Systems and Signal Processing},
  year = {2000},
  volume = {14},
  pages = {427--442},
  number = {3},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Georgiev2005,
  author = {Georgiev, P. and Theis, F. and Cichocki, A.},
  title = {Sparse component analysis and blind source separation of underdetermined
	mixtures},
  journal = {Neural Networks, {IEEE} Transactions on},
  year = {2005},
  volume = {16},
  pages = {992--996},
  number = {4},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Ghorai2010,
  author = {S.K. Ghorai and Soumya Sidhishwari and S. Konar},
  title = {Phase retrieval in optical fiber modal interference for structural
	health monitoring},
  journal = {Optics Communications},
  year = {2010},
  volume = {283},
  pages = {1278 - 1284},
  number = {7},
  __markedentry = {[Sagnik]},
  doi = {DOI: 10.1016/j.optcom.2009.12.011},
  issn = {0030-4018},
  keywords = {Phase retrieval},
  owner = {Sagnik},
  timestamp = {2011.02.21},
  url = {http://www.sciencedirect.com/science/article/B6TVF-4Y0DF9X-2/2/abbd30daf6d04ed5ca9ff9478a18e6e6}
}

@ARTICLE{Ghorai2004,
  author = {S. K. Ghorai and S. Narayan},
  title = {Data-dependent system approach for strain measurement in interferometric
	fiber optic sensor},
  journal = {Optics \& Laser Technology},
  year = {2004},
  volume = {36},
  pages = {571 - 574},
  number = {7},
  __markedentry = {[Sagnik]},
  doi = {DOI: 10.1016/j.optlastec.2004.01.003},
  issn = {0030-3992},
  keywords = {Fiber optic interferometric sensor},
  owner = {Sagnik},
  timestamp = {2011.02.21},
  url = {http://www.sciencedirect.com/science/article/B6V4H-4BS4F31-1/2/b71ffa5f11868b4cc7e65120f070d58b}
}

@BOOK{Giannakis2000,
  title = {Signal Processing Advances in Wireless and Mobile Communications,
	Volume 1: Trends in Channel Estimation and Equalization},
  publisher = {Prentice Hall {PTR}},
  year = {2000},
  author = {Giannakis, Georgios B. and Hua, Yingbo and Stoica, Petre and Tong,
	Lang},
  edition = {1st},
  month = oct,
  isbn = {0130271624},
  owner = {Sagnik},
  shorttitle = {Signal Processing Advances in Wireless and Mobile Communications,
	Volume 1},
  timestamp = {2012.02.23}
}

@ARTICLE{Giannakopoulos1998,
  author = {Giannakopoulos, X.},
  title = {Comparison of adaptive independent component analysis algorithms},
  year = {1998},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Gilli2009,
  author = {Gilli, Manfred and Winker, Peter},
  title = {Heuristic optimization methods in econometrics},
  journal = {Handbook of Computational Econometrics (DA Belsley and E. Kontoghiorghes,
	Eds.)},
  year = {2009},
  pages = {81--119}
}

@ARTICLE{Gilmore1974,
  author = {Gilmore, R.},
  title = {{Baker-Campbell-Hausdorff} formulas},
  journal = {Journal of Mathematical Physics},
  year = {1974},
  volume = {15},
  pages = {2090--2092},
  number = {12},
  month = dec,
  abstract = {{Baker-Campbell-Hausdorff} formulas can be constructed simply by matrix
	multiplication. Examples are given.},
  doi = {doi:10.1063/1.1666587},
  issn = {00222488},
  owner = {Sagnik},
  timestamp = {2012.02.23},
  url = {http://jmp.aip.org/resource/1/jmapaq/v15/i12/p2090_s1?isAuthorized=no}
}

@ARTICLE{Girolami2001,
  author = {Girolami, M.},
  title = {A variational method for learning sparse and overcomplete representations},
  journal = {Neural computation},
  year = {2001},
  volume = {13},
  pages = {2517--2532},
  number = {11},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Glisic2000,
  author = {Glisic, Branko and Badoux, Marc and Jaccoud, Jean-Paul and Inaudi,
	D},
  title = {Monitoring a subterranean structure with the SOFO system},
  journal = {Tunnel Management International magazine, ITC Ltd},
  year = {2000},
  volume = {2},
  pages = {22--27},
  number = {8}
}

@INPROCEEDINGS{glisic1999dam,
  author = {Glisic, B and Inaudi, D and Kronenberg, P and Vurpillot, S},
  title = {Dam monitoring using long SOFO sensor},
  booktitle = {Hydropower},
  year = {1999},
  volume = {10},
  pages = {18--20}
}

@BOOK{glisic2007fibre,
  title = {Fibre optic methods for structural health monitoring},
  publisher = {Wiley-Interscience},
  year = {2007},
  author = {Gli{\v{s}}i{\'c}, B. and Inaudi, D.}
}

@BOOK{Goldberg1989,
  title = {Genetic Algorithms in Search, Optimization and Machine Learning,},
  publisher = {Addison Wesley Longman Publishing Co. USA},
  year = {1989},
  author = {David E. Goldberg},
  __markedentry = {[Sagnik]},
  owner = {Welcome},
  timestamp = {2011.02.13}
}

@BOOK{Golub1996,
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  keywords = {Discrete fractional Fourier transform (DFRFT)},
  owner = {Welcome},
  timestamp = {2011.02.09},
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  year = {2003},
  owner = {Sagnik},
  timestamp = {2012.02.23}
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  number = {5},
  owner = {Sagnik},
  timestamp = {2012.02.23}
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  owner = {Sagnik},
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}

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  address = {Washington, {DC}, {USA}},
  publisher = {{IEEE} Computer Society},
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  owner = {Sagnik},
  timestamp = {2012.02.23},
  url = {http://dl.acm.org/citation.cfm?id=882492.884341}
}

@BOOK{Jain2004,
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  year = {2002},
  pages = {273--277},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Joho2003,
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  title = {Frequency domain realization of a multichannel blind deconvolution
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  booktitle = {Proc. Int. Symp. {ICA}},
  year = {2003},
  pages = {543--548},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Joshi2010,
  author = {Madhusudan Joshi and Chandra Shakher and Kehar Singh},
  title = {Image encryption using radial Hilbert transform filter bank as an
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	architecture},
  journal = {Optics and Lasers in Engineering},
  year = {2010},
  volume = {48},
  pages = {605 - 615},
  number = {5},
  __markedentry = {[Sagnik]},
  doi = {DOI: 10.1016/j.optlaseng.2009.09.014},
  issn = {0143-8166},
  keywords = {Encryption},
  owner = {Welcome},
  timestamp = {2011.02.09},
  url = {http://www.sciencedirect.com/science/article/B6V4G-4XHJX70-1/2/222ac939efca2eddc3dc6cae1b7ca931}
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@INPROCEEDINGS{Jourjine2000,
  author = {Jourjine, A. and Rickard, S. and Yilmaz, O.},
  title = {Blind separation of disjoint orthogonal signals: Demixing n sources
	from 2 mixtures},
  booktitle = {Acoustics, Speech, and Signal Processing, 2000. {ICASSP'00.} Proceedings.
	2000 {IEEE} International Conference on},
  year = {2000},
  volume = {5},
  pages = {2985--2988},
  owner = {Sagnik},
  shorttitle = {Blind separation of disjoint orthogonal signals},
  timestamp = {2012.02.23}
}

@ARTICLE{Jung2000a,
  author = {Jung, {T.P.} and Makeig, S. and Humphries, C. and Lee, {T.W.} and
	Mckeown, {M.J.} and Iragui, V. and Sejnowski, {T.J.}},
  title = {Removing electroencephalographic artifacts by blind source separation},
  journal = {Psychophysiology},
  year = {2000},
  volume = {37},
  pages = {163--178},
  number = {02},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Jung2000,
  author = {Jung, {T.P.} and Makeig, S. and Lee, {T.W.} and {McKeown}, {M.J.}
	and Brown, G. and Bell, {A.J.} and Sejnowski, {T.J.}},
  title = {Independent component analysis of biomedical signals},
  booktitle = {Proc. Int. Workshop on Independent Component Analysis and Signal
	Separation},
  year = {2000},
  pages = {633--644},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Jung2001,
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	and Lee, {T.W.} and Sejnowski, {T.J.}},
  title = {Imaging brain dynamics using independent component analysis},
  journal = {Proceedings of the {IEEE}},
  year = {2001},
  volume = {89},
  pages = {1107--1122},
  number = {7},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Jutten2004a,
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  journal = {Signal Processing},
  year = {2004},
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  pages = {217--229},
  number = {2},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Jutten1991,
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  owner = {Sagnik},
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}

@ARTICLE{Jutten2004,
  author = {Jutten, C. and Karhunen, J.},
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  number = {5},
  owner = {Sagnik},
  timestamp = {2012.02.23}
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@INPROCEEDINGS{Jutten2003,
  author = {Jutten, C. and Karhunen, J.},
  title = {Advances in nonlinear blind source separation},
  booktitle = {Proc. of the 4th Int. Symp. on Independent Component Analysis and
	Blind Signal Separation {(ICA2003)}},
  year = {2003},
  pages = {245--256},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Jutten2007,
  author = {Jutten, C. and Moussaoui, S. and Schmidt, F.},
  title = {How to Apply {ICA} on Actual Data ? Example of Mars Hyperspectral
	Image Analysis},
  booktitle = {15th International Conference on Digital Signal Processing},
  year = {2007},
  pages = {3--12},
  month = jul,
  publisher = {{IEEE}},
  abstract = {As any estimation method, results provided by {ICA} are dependent
	of a model - usually a linear mixture and separation model - and
	of a criterion - usually independence. In many actual problems, the
	model is a coarse approximation of the system physics and independence
	can be more or less satisfied, and consequently results are not reliable.
	Moreover, with many actual data, there is a lack of reliable knowledge
	on the sources to be extracted, and the interpretation of the independent
	components {(IC)} must be done very carefully, using partial prior
	information and with interactive discussions with experts. In this
	talk, we explain how such a scientific method can take place on the
	example of analysis of Mars hyperspectral images.},
  doi = {10.1109/ICDSP.2007.4288502},
  isbn = {1-4244-0882-2},
  keywords = {astronomical image processing, Bayesian source separation, Biomedical
	signal processing, hyperspectral image analysis, hyperspectral images,
	Hyperspectral imaging, Hyperspectral sensors, Image analysis, Independent
	component analysis, linear mixture, Mars, Mars Express, Mars hyperspectral
	images, Parametric statistics, Physics, positivity, separation model,
	Signal processing algorithms, Source separation},
  owner = {Sagnik},
  shorttitle = {How to Apply {ICA} on Actual Data ?},
  timestamp = {2012.02.23}
}

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  owner = {Sagnik},
  timestamp = {2012.02.23},
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	Oja, E.},
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@ARTICLE{Karhunen1994,
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	separation, feedforward neural nets, Higher order statistics, image
	processing, Independent component analysis, multilayer feedforward
	networks, Neural networks, neural structures, Principal component
	analysis, Robustness, Signal processing, Signal processing algorithms,
	statistical analysis, Unsupervised learning, Vectors},
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@ARTICLE{Karhunen1998,
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  journal = {Neurocomputing},
  year = {1998},
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  shorttitle = {The nonlinear {PCA} criterion in blind source separation},
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@ARTICLE{Kesavan2010,
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  number = {2},
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  keywords = {Fiber optic sensor},
  owner = {Sagnik},
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@ARTICLE{Kopriva2008,
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	sources},
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@ARTICLE{Kopriva2008a,
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	sources},
  journal = {Neurocomputing},
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	European Symposium on Artificial Neural Networks 2007},
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@ARTICLE{Kreutz-Delgado2003,
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	K. and Lee, {T.W.} and Sejnowski, {T.J.}},
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@ARTICLE{Kumar2008,
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@ARTICLE{Kuruoglu2010,
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@INPROCEEDINGS{Lacoume1988,
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	1988},
  year = {1988},
  pages = {199--203},
  month = aug,
  publisher = {{IEEE}},
  abstract = {It is noted that the problem of source separation has no solution
	without a priori information when only the spectral matrix is used.
	The authors have developed an algorithm using the fourth-order cumulants
	that solves the problem of the two-source separation without the
	necessity of a priori information. They show that, in the case of
	two sources and two sensors, the model is described by two parameters.
	They then present the identification of these two parameters with
	the cumulants up to order 4. The potentialities of this source-identification
	algorithm are illustrated using simulated data},
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  keywords = {Acoustic sensors, Array signal processing, cumulants, Filtering, identification,
	information theory, matrix algebra, parameter estimation, parameter
	identification, Sensor arrays, Signal processing, Source separation,
	sources identification, spectral matrix, Statistics, Stochastic processes,
	Underwater acoustics, Underwater vehicles},
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@ARTICLE{Lee1997a,
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@INPROCEEDINGS{Lee1997,
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@ARTICLE{Lee1999,
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@INPROCEEDINGS{Li2003,
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  owner = {Sagnik},
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@ARTICLE{Li1996,
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@ARTICLE{Linsker1992,
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	its output and the signal portion of its input (which is admixed
	with noise) is useful for extracting salient input features, and
	may provide a model for aspects of biological neural network function.
	I describe a local synaptic Learning rule that performs stochastic
	gradient ascent in this information-theoretic quantity, for the case
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	and noise are multivariate gaussian. Feedforward connection strengths
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	examples of noise alone are presented. Each recurrent lateral connection
	has two values of connection strength, one for each phase; these
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@BOOK{Lipschutz1997,
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@ARTICLE{Liu1996,
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@ARTICLE{Makeig1996,
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@ARTICLE{Makeig2004,
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@ARTICLE{Mallat1993,
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@ARTICLE{Mansour1995,
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  title = {Fourth-order criteria for blind sources separation},
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}

@ARTICLE{Mansour2000,
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@ARTICLE{Marc'AurelioRanzato2006,
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	model},
  journal = {Advances in neural information processing systems},
  year = {2006},
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@ARTICLE{Mateo2009,
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  number = {4},
  __markedentry = {[Sagnik]},
  doi = {DOI: 10.1016/j.eswa.2008.11.029},
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  keywords = {Speckle noise},
  owner = {Sagnik},
  timestamp = {2011.05.25},
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@ARTICLE{Matsuoka1995,
  author = {Matsuoka, Kiyotoshi and Ohoya, Masahiro and Kawamoto, Mitsuru},
  title = {A neural net for blind separation of nonstationary signals},
  journal = {Neural Networks},
  year = {1995},
  volume = {8},
  pages = {411--419},
  number = {3},
  abstract = {This paper proposes a neural network that recovers some original random
	signals from their linear mixtures observed by the same number of
	sensors. The network acquires the function with a learning process
	without using any particular information about the statistical properties
	of the sources and the coefficients of the linear transformation,
	except the fact that the source signals are statistically independent
	and nonstationary. The learning rule for the network's parameters
	is derived from the steepest descent minimization of a time-dependent
	cost function that takes the minimum only when the network outputs
	are uncorrelated with each other.},
  doi = {10.1016/0893-6080(94)00083-X},
  issn = {0893-6080},
  keywords = {{Anti-Hebbian} learning, blind separation, Nonstationary signals,
	Self-organization},
  owner = {Sagnik},
  timestamp = {2012.02.23},
  url = {http://www.sciencedirect.com/science/article/pii/089360809400083X}
}

@ARTICLE{McKeown1998,
  author = {{McKeown}, M J and Jung, T P and Makeig, S and Brown, G and Kindermann,
	S S and Lee, T W and Sejnowski, T J},
  title = {Spatially independent activity patterns in functional {MRI} data
	during the stroop color-naming task},
  journal = {Proceedings of the National Academy of Sciences of the United States
	of America},
  year = {1998},
  volume = {95},
  pages = {803--810},
  number = {3},
  month = feb,
  note = {{PMID:} 9448244},
  abstract = {A method is given for determining the time course and spatial extent
	of consistently and transiently task-related activations from other
	physiological and artifactual components that contribute to functional
	{MRI} {(fMRI)} recordings. Independent component analysis {(ICA)}
	was used to analyze two {fMRI} data sets from a subject performing
	6-min trials composed of alternating 40-sec Stroop color-naming and
	control task blocks. Each component consisted of a fixed three-dimensional
	spatial distribution of brain voxel values (a "map") and an associated
	time course of activation. For each trial, the algorithm detected,
	without a priori knowledge of their spatial or temporal structure,
	one consistently task-related component activated during each Stroop
	task block, plus several transiently task-related components activated
	at the onset of one or two of the Stroop task blocks only. Activation
	patterns occurring during only part of the {fMRI} trial are not observed
	with other techniques, because their time courses cannot easily be
	known in advance. Other {ICA} components were related to physiological
	pulsations, head movements, or machine noise. By using higher-order
	statistics to specify stricter criteria for spatial independence
	between component maps, {ICA} produced improved estimates of the
	temporal and spatial extent of task-related activation in our data
	compared with principal component analysis {(PCA).} {ICA} appears
	to be a promising tool for exploratory analysis of {fMRI} data, particularly
	when the time courses of activation are not known in advance.},
  issn = {0027-8424},
  keywords = {algorithms, Brain, Brain Mapping, Color Perception Tests, Humans,
	Magnetic Resonance Imaging, Models, Neurological, Psychomotor Performance,
	Statistics as Topic},
  owner = {Sagnik},
  timestamp = {2012.02.23},
  url = {http://www.ncbi.nlm.nih.gov/pubmed/9448244}
}

@TECHREPORT{McKeown1997,
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  institution = {{DTIC} Document},
  year = {1997},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{McKeown2003,
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  pages = {620--629},
  number = {5},
  owner = {Sagnik},
  shorttitle = {Independent component analysis of functional {MRI}},
  timestamp = {2012.02.23}
}

@ARTICLE{Mendlovic1993,
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  number = {9},
  owner = {Sagnik},
  shorttitle = {Fractional Fourier transforms and their optical implementation},
  timestamp = {2012.02.23}
}

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  pages = {303--309},
  number = {2},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

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}

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  year = {2001},
  volume = {48},
  pages = {111--116},
  number = {1},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

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  year = {2000},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

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  year = {2007},
  owner = {Sagnik},
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  timestamp = {2012.02.23}
}

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  owner = {Sagnik},
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  year = {2003},
  volume = {27},
  pages = {511 - 521},
  number = {10},
  __markedentry = {[Sagnik]},
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  issn = {0141-9331},
  keywords = {Fourier transform},
  owner = {Welcome},
  timestamp = {2011.02.13},
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  doi = {DOI: 10.1016/j.neucom.2008.04.016},
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  owner = {Sagnik},
  timestamp = {2011.05.25},
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}

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  owner = {Sagnik},
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}

@ARTICLE{Oja1997,
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  journal = {Neurocomputing},
  year = {1997},
  volume = {17},
  pages = {25--45},
  number = {1},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@BOOK{Oja1995,
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	analysis},
  publisher = {Helsinki University of Technology},
  year = {1995},
  author = {Oja, E.},
  owner = {Sagnik},
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  timestamp = {2012.02.23}
}

@BOOK{Oja2001,
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  year = {2001},
  author = {Oja, E. and Hyvarinen, A. and Karhunen, J.},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Oja1995a,
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  pages = {83--97},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

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  booktitle = {4th International Symposium on Independent Component Analysis and
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  __markedentry = {[Sagnik]},
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@ARTICLE{Olshausen1997,
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  number = {6},
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@ARTICLE{Ozaktas1994,
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@ARTICLE{Ozaktas1995,
  author = {Ozaktas, {H.M.} and Mendlovic, D.},
  title = {Fractional Fourier optics},
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  volume = {12},
  pages = {743--751},
  number = {4},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Ozaktas1994a,
  author = {Ozaktas, {H.M.} and Mendlovic, D.},
  title = {Fractional Fourier transform as a tool for analyzing beam propagation
	and spherical mirror resonators},
  journal = {Optics letters},
  year = {1994},
  volume = {19},
  pages = {1678--1680},
  number = {21},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Ozaktas1993,
  author = {Ozaktas, {H.M.} and Mendlovic, D.},
  title = {Fractional Fourier transforms and their optical implementation. {II}},
  journal = {{JOSA} A},
  year = {1993},
  volume = {10},
  pages = {2522--2531},
  number = {12},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Ozaktas1993a,
  author = {Ozaktas, {H.M.} and Mendlovic, D.},
  title = {Fourier transforms of fractional order and their optical interpretation},
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  pages = {163--169},
  number = {3-4},
  owner = {Sagnik},
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}

@ARTICLE{Pajunen1996,
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  title = {Nonlinear Independent Component Analysis by {Self-Organizing} Maps},
  journal = {{Neural} {Networks}},
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  volume = {12},
  pages = {429---439},
  owner = {Sagnik},
  timestamp = {2012.02.23},
  url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.55.2938}
}

@ARTICLE{Pajunen1997,
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  title = {A maximum likelihood approach to nonlinear blind source separation},
  journal = {Artificial Neural {Networks---ICANN'97}},
  year = {1997},
  pages = {541--546},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@BOOK{Papoulis1991,
  title = {Probability, Random Variables, and Stochastic Processes},
  publisher = {{McGraw} Hill Higher Education},
  year = {1991},
  author = {Papoulis, Athanansios},
  edition = {3rd edition},
  month = mar,
  isbn = {0070484775},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Papy2005,
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  title = {Exponential data fitting using multilinear algebra: the single-channel
	and multi-channel case},
  journal = {Numerical linear algebra with applications},
  year = {2005},
  volume = {12},
  pages = {809--826},
  number = {8},
  owner = {Sagnik},
  shorttitle = {Exponential data fitting using multilinear algebra},
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}

@ARTICLE{Parra2003,
  author = {Parra, L. and Sajda, P.},
  title = {Blind source separation via generalized eigenvalue decomposition},
  journal = {The Journal of Machine Learning Research},
  year = {2003},
  volume = {4},
  pages = {1261--1269},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Parra2000,
  author = {Parra, L. and Spence, C.},
  title = {Convolutive blind separation of non-stationary sources},
  journal = {Speech and Audio Processing, {IEEE} Transactions on},
  year = {2000},
  volume = {8},
  pages = {320--327},
  number = {3},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Parra1998,
  author = {Parra, L. and Spence, C. and De Vries, B.},
  title = {Convolutive blind source separation based on multiple decorrelation},
  booktitle = {Neural Networks for Signal Processing {VIII}, 1998. Proceedings of
	the 1998 {IEEE} Signal Processing Society Workshop},
  year = {1998},
  pages = {23--32},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Pedersen,
  author = {Pedersen, Michael Syskind and Larsen, Jan and Kjems, Ulrik and Parra,
	Lucas C},
  title = {A {SURVEY} {OF} {CONVOLUTIVE} {BLIND} {SOURCE} {SEPARATION} {METHODS}},
  journal = {{SPRINGER} {HANDBOOK} {ON} {SPEECH} {PROCESSING} {AND} {SPEECH} {COMMUNICATION}},
  owner = {Sagnik},
  timestamp = {2012.02.23},
  url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.68.4632}
}

@ARTICLE{Pedersen2007,
  author = {Pedersen, {M.S.} and Larsen, J. and Kjems, U. and Parra, {L.C.}},
  title = {A survey of convolutive blind source separation methods},
  journal = {Multichannel Speech Processing Handbook},
  year = {2007},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Pei1998,
  author = {Soo-Chang Pei and Min-Hung Yeh},
  title = {Two dimensional discrete fractional Fourier transform},
  journal = {Signal Processing},
  year = {1998},
  volume = {67},
  pages = {99 - 108},
  number = {1},
  __markedentry = {[Sagnik]},
  doi = {DOI: 10.1016/S0165-1684(98)00024-3},
  issn = {0165-1684},
  keywords = {Fourier transform},
  owner = {Sagnik},
  timestamp = {2011.02.21},
  url = {http://www.sciencedirect.com/science/article/B6V18-3VXYRBR-H/2/b471baed80edbbaa434fe269fa80ca34}
}

@ARTICLE{Penny2001,
  author = {Penny, W. and Everson, R. and Roberts, S.},
  title = {{ICA:} model order selection and dynamic source models},
  journal = {Independent component analysis: Principles and practice},
  year = {2001},
  pages = {299--314},
  owner = {Sagnik},
  shorttitle = {{ICA}},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Peters2003,
  author = {Peters, J. and Vijayakumar, S. and Schaal, S.},
  title = {Reinforcement learning for humanoid robotics},
  booktitle = {Proceedings of the third {IEEE-RAS} international conference on humanoid
	robots},
  year = {2003},
  pages = {1--20},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Pezzella2008,
  author = {F. Pezzella and G. Morganti and G. Ciaschetti},
  title = {A genetic algorithm for the Flexible Job-shop Scheduling Problem},
  journal = {Computers \& Operations Research},
  year = {2008},
  volume = {35},
  pages = {3202 - 3212},
  number = {10},
  note = {Part Special Issue: Search-based Software Engineering},
  __markedentry = {[Sagnik]},
  doi = {DOI: 10.1016/j.cor.2007.02.014},
  issn = {0305-0548},
  keywords = {Job-shop Scheduling},
  owner = {Welcome},
  timestamp = {2011.02.13},
  url = {http://www.sciencedirect.com/science/article/B6VC5-4N5CXN3-2/2/c9a98deff96cc5022beeefb60544d26a}
}

@ARTICLE{Pham2001,
  author = {Pham, {D.T.}},
  title = {Blind separation of instantaneous mixture of sources via the Gaussian
	mutual information criterion},
  journal = {Signal Processing},
  year = {2001},
  volume = {81},
  pages = {855--870},
  number = {4},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Pham2001a,
  author = {Pham, {D.T.} and Cardoso, {J.F.}},
  title = {Blind separation of instantaneous mixtures of nonstationary sources},
  journal = {Signal Processing, {IEEE} Transactions on},
  year = {2001},
  volume = {49},
  pages = {1837--1848},
  number = {9},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Pham1997,
  author = {Pham, {D.T.} and Garat, P.},
  title = {Blind separation of mixture of independent sources through a quasi-maximum
	likelihood approach},
  journal = {Signal Processing, {IEEE} Transactions on},
  year = {1997},
  volume = {45},
  pages = {1712--1725},
  number = {7},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Piccard1918,
  author = {Piccard, Jean},
  title = {Couleurs de second ordre},
  year = {1918},
  volume = {1},
  pages = {134--135},
  number = {1},
  doi = {10.1002/hlca.19180010112},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Pierre1994,
  author = {Pierre, Comon},
  title = {Independent component analysis, A new concept?},
  journal = {Signal Processing},
  year = {1994},
  volume = {36},
  pages = {287--314},
  number = {3},
  month = apr,
  abstract = {The independent component analysis {(ICA)} of a random vector consists
	of searching for a linear transformation that minimizes the statistical
	dependence between its components. In order to define suitable search
	criteria, the expansion of mutual information is utilized as a function
	of cumulants of increasing orders. An efficient algorithm is proposed,
	which allows the computation of the {ICA} of a data matrix within
	a polynomial time. The concept of {ICA} may actually be seen as an
	extension of the principal component analysis {(PCA)}, which can
	only impose independence up to the second order and, consequently,
	defines directions that are orthogonal. Potential applications of
	{ICA} include data analysis and compression, Bayesian detection,
	localization of sources, and blind identification and deconvolution.},
  doi = {10.1016/0165-1684(94)90029-9},
  issn = {0165-1684},
  owner = {Sagnik},
  timestamp = {2012.02.23},
  url = {http://www.sciencedirect.com/science/article/pii/0165168494900299}
}

@ARTICLE{Plett2003,
  author = {Plett, {G.L.}},
  title = {Adaptive inverse control of linear and nonlinear systems using dynamic
	neural networks},
  journal = {Neural Networks, {IEEE} Transactions on},
  year = {2003},
  volume = {14},
  pages = {360--376},
  number = {2},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Plumbley2003,
  author = {Plumbley, M. D},
  title = {Algorithms for nonnegative independent component analysis},
  journal = {{IEEE} Transactions on Neural Networks},
  year = {2003},
  volume = {14},
  pages = {534-- 543},
  number = {3},
  month = may,
  abstract = {We consider the task of solving the independent component analysis
	{(ICA)} problem {x=As} given observations x, with a constraint of
	nonnegativity of the source random vector s. We refer to this as
	nonnegative independent component analysis and we consider methods
	for solving this task. For independent sources with nonzero probability
	density function (pdf) p(s) down to s=0 it is sufficient to find
	the orthonormal rotation {y=Wz} of prewhitened sources {z=Vx}, which
	minimizes the mean squared error of the reconstruction of z from
	the rectified version y+ of y. We suggest some algorithms which perform
	this, both based on a nonlinear principal component analysis {(PCA)}
	approach and on a geodesic search method driven by differential geometry
	considerations. We demonstrate the operation of these algorithms
	on an image separation problem, which shows in particular the fast
	convergence of the rotation and geodesic methods and apply the approach
	to a musical audio analysis task.},
  doi = {10.1109/TNN.2003.810616},
  issn = {1045-9227},
  keywords = {Algorithm design and analysis, differential geometry, geodesic search,
	Image analysis, Image reconstruction, image separation problem, Independent
	component analysis, mean squared error, musical audio analysis task,
	neural nets, Neural networks, nonnegative independent component analysis,
	nonzero probability density function, Principal component analysis,
	Probability density function, Search methods, Signal processing,
	Signal processing algorithms, source random vector, Stiefel manifold,
	Vectors},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@TECHREPORT{Porrill1997,
  author = {Porrill, J. and Stone, J.},
  title = {Independent components analysis for signal separation and dimension
	reduction},
  institution = {Citeseer},
  year = {1997},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@TECHREPORT{Porrill1998,
  author = {Porrill, J. and Stone, {J.V.}},
  title = {Undercomplete independent component analysis for signal separation
	and dimension reduction},
  institution = {Citeseer},
  year = {1998},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Praly2003,
  author = {Praly, L.},
  title = {Asymptotic stabilization via output feedback for lower triangular
	systems with output dependent incremental rate},
  journal = {Automatic Control, {IEEE} Transactions on},
  year = {2003},
  volume = {48},
  pages = {1103--1108},
  number = {6},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Principe1993,
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  title = {{THE} {GAMMA} {FILTER} - A New Class of Adaptive {IIR} Filters with
	Restricted Feedback},
  journal = {{IEEE} {TRANSACTIONS} {ON} {SIGNAL} {PROCESSING}},
  year = {1993},
  volume = {41},
  pages = {649---656},
  owner = {Sagnik},
  timestamp = {2012.02.23},
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}

@INPROCEEDINGS{Principe1996,
  author = {Principe, {J.C.} and Wang, C. and Wu, {H.C.}},
  title = {Temporal decorrelation using teacher forcing {anti-Hebbian} learning
	and its application in adaptive blind source separation},
  booktitle = {Neural Networks for Signal Processing [1996] {VI.} Proceedings of
	the 1996 {IEEE} Signal Processing Society Workshop},
  year = {1996},
  pages = {413--422},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@BOOK{R.L.Haupt2004,
  title = {Practical Genetic Algorithms},
  publisher = {Wiley-Interscience, USA},
  year = {2004},
  author = {R. L. Haupt, S. E. Haupt},
  __markedentry = {[Sagnik]},
  owner = {Welcome},
  timestamp = {2011.02.13}
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@ARTICLE{Raiko2006,
  author = {Raiko, T. and Tornio, M. and Honkela, A. and Karhunen, J.},
  title = {State inference in variational Bayesian nonlinear state-space models},
  journal = {Independent Component Analysis and Blind Signal Separation},
  year = {2006},
  pages = {222--229},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Rao1999,
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  year = {1999},
  volume = {8},
  pages = {355},
  number = {4},
  publisher = {IOP Publishing}
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@INPROCEEDINGS{Reyes-Gomez2003,
  author = {{Reyes-Gomez}, {M.J.} and Bhiksha, R. and Ellis, {D.P.W.}},
  title = {Multi-channel source separation by beamforming trained with factorial
	{HMMs}},
  booktitle = {Applications of Signal Processing to Audio and Acoustics, 2003 {IEEE}
	Workshop on.},
  year = {2003},
  pages = {13--16},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{RicardoNuno1997,
  author = {Ricardo Nuno, Vig\'ario},
  title = {Extraction of ocular artefacts from {EEG} using independent component
	analysis},
  journal = {Electroencephalography and Clinical Neurophysiology},
  year = {1997},
  volume = {103},
  pages = {395--404},
  number = {3},
  month = sep,
  abstract = {Eye activity is one of the main sources of artefacts in {EEG} and
	{MEG} recordings. A new approach to the correction of these disturbances
	is presented using the statistical technique of independent component
	analysis. This technique separates components by the kurtosis of
	their amplitude distribution over time, thereby distinguishing between
	strictly periodical signals, regularly occurring signals and irregularly
	occurring signals. The latter category is usually formed by artefacts.
	Through this approach, it is possible to isolate pure eye activity
	in the {EEG} recordings (including {EOG} channels), and so reduce
	the amount of brain activity that is subtracted from the measurements,
	when extracting portions of the {EOG} signals.},
  doi = {10.1016/S0013-4694(97)00042-8},
  issn = {0013-4694},
  keywords = {Blind source separation {(BSS)}, {EEG}, {EOG}, Independent component
	analysis {(ICA)}, Ocular artefact correction},
  owner = {Sagnik},
  timestamp = {2012.02.23},
  url = {http://www.sciencedirect.com/science/article/pii/S0013469497000428}
}

@ARTICLE{Ridgway1988,
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	of {BOLD} signals},
  journal = {{NeuroImage}},
  year = {2004},
  volume = {21},
  pages = {547--567},
  number = {2},
  owner = {Sagnik},
  shorttitle = {A state-space model of the hemodynamic approach},
  timestamp = {2012.02.23}
}

@ARTICLE{Roan2002,
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	gear tooth failure detection and analysis},
  journal = {Mechanical Systems and Signal Processing},
  year = {2002},
  volume = {16},
  pages = {719--740},
  number = {5},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Robila2002,
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  title = {A fast source separation algorithm for hyperspectral image processing},
  booktitle = {Geoscience and Remote Sensing Symposium, 2002. {IGARSS'02.} 2002
	{IEEE} International},
  year = {2002},
  volume = {6},
  pages = {3516--3518},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Rojas2004,
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	Rojas, I. and {Mart{\textbackslash}textbackslash'in-Clemente}, R.},
  title = {Blind source separation in post-nonlinear mixtures using competitive
	learning, simulated annealing, and a genetic algorithm},
  journal = {Systems, Man, and Cybernetics, Part C: Applications and Reviews,
	{IEEE} Transactions on},
  year = {2004},
  volume = {34},
  pages = {407--416},
  number = {4},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

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  volume = {37},
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  number = {11},
  owner = {Sagnik},
  timestamp = {2012.02.23}
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  title = {Blind source recovery: algorithms for static and dynamic environments},
  booktitle = {Neural Networks, 2001. Proceedings. {IJCNN'01.} International Joint
	Conference on},
  year = {2001},
  volume = {2},
  pages = {902--907},
  owner = {Sagnik},
  shorttitle = {Blind source recovery},
  timestamp = {2012.02.23}
}

@ARTICLE{Salem2007,
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	Georges},
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	des statistiques de second ordre},
  journal = {Majecstic},
  year = {2007},
  pages = {191--198},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Salerno2004,
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  booktitle = {{Knowledge-Based} Intelligent Information and Engineering Systems},
  year = {2004},
  pages = {426--432},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Salustri2005,
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	source separation},
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  year = {2005},
  volume = {52},
  pages = {1140--1142},
  number = {6},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Santoso1996,
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  year = {1996},
  volume = {11},
  pages = {924--930},
  number = {2},
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@ARTICLE{saxena2005fractional,
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  pages = {11--26}
}

@ARTICLE{Scholkopf1998,
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  title = {Nonlinear component analysis as a kernel eigenvalue problem},
  journal = {Neural computation},
  year = {1998},
  volume = {10},
  pages = {1299--1319},
  number = {5},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Schetinin2007,
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	and Salerno, E. and Bedini, L. and Kuruoglu, E. and Tonazzini, A.
	and Zazula, D. and Cigale, B. and others},
  title = {4 Advanced Feature Recognition and Classification Using Artificial
	Intelligence Paradigms},
  journal = {Artificial Intelligence in Recognition and Classification of Astrophysical
	and Medical Images},
  year = {2007},
  pages = {151--338},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Schobben1999,
  author = {Schobben, D. and Torkkola, K. and Smaragdis, P.},
  title = {Evaluation of blind signal separation methods},
  booktitle = {Proc. Int. Workshop on {ICA} and {BSS} {(ICA'99}},
  year = {1999},
  pages = {261--266},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Sejdic2010,
  author = {Ervin Sejdic and Igor Djurovic and LJubisa Stankovic},
  title = {Fractional Fourier transform as a signal processing tool: An overview
	of recent developments},
  journal = {Signal Processing},
  year = {2010},
  volume = {In Press, Corrected Proof},
  pages = { - },
  __markedentry = {[Sagnik]},
  doi = {DOI: 10.1016/j.sigpro.2010.10.008},
  issn = {0165-1684},
  keywords = {Fractional Fourier transform},
  owner = {Sagnik},
  timestamp = {2011.02.21},
  url = {http://www.sciencedirect.com/science/article/B6V18-51962R0-1/2/0c8a52bdd033cdd9c7329bce262fc38b}
}

@ARTICLE{Sejnowski1995,
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  year = {1995},
  volume = {7},
  pages = {1129--1159},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@BOOK{Sejnowski1999,
  title = {Unsupervised learning: foundations of neural computation},
  publisher = {The {MIT} Press},
  year = {1999},
  author = {Sejnowski, {T.J.}},
  owner = {Sagnik},
  shorttitle = {Unsupervised learning},
  timestamp = {2012.02.23}
}

@ARTICLE{Serbes2011,
  author = {Ahmet Serbes and Lutfiye Durak-Ata},
  title = {The discrete fractional Fourier transform based on the DFT matrix},
  journal = {Signal Processing},
  year = {2011},
  volume = {91},
  pages = {571 - 581},
  number = {3},
  note = {Advances in Fractional Signals and Systems},
  __markedentry = {[Sagnik]},
  doi = {DOI: 10.1016/j.sigpro.2010.05.007},
  issn = {0165-1684},
  keywords = {Discrete fractional fourier transform},
  owner = {Sagnik},
  timestamp = {2011.02.21},
  url = {http://www.sciencedirect.com/science/article/B6V18-50393MS-1/2/27ca20fd65a0fd3db3d2895129b4f77c}
}

@ARTICLE{Shalvi1993,
  author = {Shalvi, O. and Weinstein, E.},
  title = {Super-exponential methods for blind deconvolution},
  journal = {Information Theory, {IEEE} Transactions on},
  year = {1993},
  volume = {39},
  pages = {504--519},
  number = {2},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Shalvi1990,
  author = {Shalvi, O. and Weinstein, E.},
  title = {New criteria for blind deconvolution of nonminimum phase systems
	(channels)},
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  year = {1990},
  volume = {36},
  pages = {312--321},
  number = {2},
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@BOOK{shannon1962mathematical,
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@ARTICLE{Shi2004,
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  title = {A new fixed-point algorithm for independent component analysis},
  journal = {Neurocomputing},
  year = {2004},
  volume = {56},
  pages = {467--473},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Shynk1990,
  author = {Shynk, J. J and Chan, C. K and Petraglia, M. R},
  title = {Blind adaptive filtering in the frequency domain},
  booktitle = {, {IEEE} International Symposium on Circuits and Systems, 1990},
  year = {1990},
  pages = {275--278 vol.1},
  month = may,
  publisher = {{IEEE}},
  abstract = {Efficient block implementations which are based on frequency-domain
	techniques of the constant modulus and the P-vector least-mean-square
	blind algorithms are described. These realizations have much less
	computational complexity than nonblock time-domain methods, and they
	can have improved convergence properties. Although several implementations
	are possible, including filter-bank and multirate structures, only
	linear convolution methods are used. A frequency-domain realization
	of a T/2-spaced constant modulus algorithm equalizer is examined,
	and computer simulations are presented},
  doi = {10.1109/ISCAS.1990.112008},
  keywords = {Adaptive algorithm, Adaptive filters, block implementations, computational
	complexity, Computer errors, constant modulus, convergence, convergence
	properties, Convolution, Estimation error, filtering and prediction
	theory, frequency domain, Frequency domain analysis, frequency-domain
	analysis, frequency-domain realization, Information processing, Least
	squares approximation, linear convolution methods, P-vector least-mean-square
	blind algorithms, Signal processing},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Sidiropoulos2000,
  author = {Sidiropoulos, {N.D.} and Bro, R. and Giannakis, {G.B.}},
  title = {Parallel factor analysis in sensor array processing},
  journal = {Signal Processing, {IEEE} Transactions on},
  year = {2000},
  volume = {48},
  pages = {2377--2388},
  number = {8},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Sidiropoulos1998,
  author = {Sidiropoulos, {N.D.} and Giannakis, {G.B.} and Bro, R.},
  title = {Deterministic waveform-preserving blind separation of {DS-CDMA} signals
	using an antenna array},
  booktitle = {Statistical Signal and Array Processing, 1998. Proceedings., Ninth
	{IEEE} {SP} Workshop on},
  year = {1998},
  pages = {304--307},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Sigl1994,
  author = {Sigl, {J.C.} and Chamoun, {N.G.}},
  title = {An introduction to bispectral analysis for the electroencephalogram},
  journal = {Journal of Clinical Monitoring and Computing},
  year = {1994},
  volume = {10},
  pages = {392--404},
  number = {6},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Signal1990,
  author = {Signal, {J.S.L.T.D.}},
  title = {Image Processing},
  booktitle = {Proc. Int'l Optical Computing Conf},
  year = {1990},
  volume = {1},
  pages = {1977},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Slock1996,
  author = {Slock, D. {T.M}},
  title = {Spatio-temporal training-sequence based channel equalization and
	adaptive interference cancellation},
  booktitle = {{IEEE} International Conference on Acoustics, Speech, and Signal
	Processing, {ICASSP-96.}},
  year = {1996},
  volume = {5},
  pages = {2714--2717 vol. 5},
  month = may,
  publisher = {{IEEE}},
  abstract = {We consider mobile radio communications with one user of interest
	and possibly interfering users and noise, over several discrete-time
	channels obtained either by oversampling or from multiple antennas.
	The optimal receiver structure for one signal of interest plus spatially
	and temporally correlated noise is {MLSE} equalization with an appropriately
	weighted metric for vector signals. We show however that we can alternatively
	pass the vector received signal through both a {MISO} (multi-input
	single output) matched filter and a {MIMO} blocking equalizer. The
	blocking equalizer output is independent of the signal of interest
	and is used as the input to a {MISO} Wiener filter that reduces the
	noise in the matched filter output. The training sequence of the
	signal of interest can be used to estimate the corresponding channel,
	from which the matched filter and blocking equalizer can be determined.
	The remaining quantities can be adapted from the available signals},
  doi = {10.1109/ICASSP.1996.550113},
  isbn = {0-7803-3192-3},
  keywords = {adaptive interference cancellation, adaptive signal processing, discrete
	time systems, discrete-time channels, equalisers, Equalizers, interference
	suppression, interfering users, Land mobile radio, matched filter,
	Matched filters, Maximum likelihood estimation, {MIMO}, {MIMO} blocking
	equalizer, {MIMO} systems, {MISO}, {MLSE} equalization, Mobile antennas,
	Mobile communication, mobile radio communications, multi-input single
	output, multiple antennas, noise, Noise reduction, optimal receiver
	structure, oversampling, radio receivers, radiofrequency interference,
	Receivers, spatio-temporal training-sequence based channel equalization,
	telecommunication channels, weighted metric, Wiener filter, Wiener
	filters},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Smaragdis1998,
  author = {Smaragdis, P. and others},
  title = {Blind separation of convolved mixtures in the frequency domain},
  journal = {Neurocomputing},
  year = {1998},
  volume = {22},
  pages = {21--34},
  number = {1},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Smith2004,
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	{C.F.} and Behrens, {T.E.J.} and {Johansen-Berg}, H. and Bannister,
	{P.R.} and De Luca, M. and Drobnjak, I. and Flitney, {D.E.} and others},
  title = {Advances in functional and structural {MR} image analysis and implementation
	as {FSL}},
  journal = {Neuroimage},
  year = {2004},
  volume = {23},
  pages = {S208--S219},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@BOOK{Stallings2003,
  title = {Data and Computer Communications},
  publisher = {Pearson Education},
  year = {2003},
  author = {W. Stallings},
  owner = {Sagnik},
  timestamp = {2013.03.03}
}

@ARTICLE{Stockwell1996,
  author = {Stockwell, {RG} and Mansinha, L. and Lowe, {RP}},
  title = {Localization of the complex spectrum: the S transform},
  journal = {Signal Processing, {IEEE} Transactions on},
  year = {1996},
  volume = {44},
  pages = {998--1001},
  number = {4},
  owner = {Sagnik},
  shorttitle = {Localization of the complex spectrum},
  timestamp = {2012.02.23}
}

@BOOK{stone2004independent,
  title = {Independent component analysis: a tutorial introduction},
  publisher = {The MIT Press},
  year = {2004},
  author = {Stone, J.V.}
}

@ARTICLE{Stone2001,
  author = {Stone, {J.V.}},
  title = {Blind source separation using temporal predictability},
  journal = {Neural computation},
  year = {2001},
  volume = {13},
  pages = {1559--1574},
  number = {7},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Stone2002,
  author = {Stone, {JV} and Porrill, J. and Porter, {NR} and Wilkinson, {ID}},
  title = {Spatiotemporal independent component analysis of event-related {fMRI}
	data using skewed probability density functions},
  journal = {{NeuroImage}},
  year = {2002},
  volume = {15},
  pages = {407--421},
  number = {2},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Su2005,
  author = {Su, {C.Y.} and Wang, Q. and Chen, X. and Rakheja, S.},
  title = {Adaptive variable structure control of a class of nonlinear systems
	with unknown {Prandtl-Ishlinskii} hysteresis},
  journal = {Automatic Control, {IEEE} Transactions on},
  year = {2005},
  volume = {50},
  pages = {2069--2074},
  number = {12},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Sun2001,
  author = {Sun, X. and Douglas, S.},
  title = {A natural gradient convolutive blind source separation algorithm
	for speech mixtures},
  booktitle = {Proc. {ICA}},
  year = {2001},
  volume = {1},
  pages = {59--64},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@CONFERENCE{Szu2003,
  author = {H. Szu and I. Koperiva},
  title = {Deterministic Blind Source Separation for Space Variant Imaging},
  booktitle = {4th International Symposium on Independent Component Analysis and
	Blind Source Separation (ICA 2003), Nara, Japan},
  year = {2003},
  __markedentry = {[Sagnik]},
  owner = {Sagnik},
  timestamp = {2011.02.16}
}

@ARTICLE{sanchez2002frontiers,
  author = {S{\'a}nchez, A and David, V},
  title = {Frontiers of research in BSS/ICA},
  journal = {Neurocomputing},
  year = {2002},
  volume = {49},
  pages = {7--23},
  number = {1},
  publisher = {Elsevier}
}

@ARTICLE{Taleb1999,
  author = {Taleb, A. and Jutten, C.},
  title = {Source separation in post-nonlinear mixtures},
  journal = {Signal Processing, {IEEE} Transactions on},
  year = {1999},
  volume = {47},
  pages = {2807--2820},
  number = {10},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Taleb1997,
  author = {Taleb, A. and Jutten, C.},
  title = {Nonlinear source separation: The post-nonlinear mixtures},
  booktitle = {European symposium on artificial neural networks},
  year = {1997},
  pages = {279--284},
  owner = {Sagnik},
  shorttitle = {Nonlinear source separation},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Taleb1998,
  author = {Taleb, A. and Jutten, C. and Olympieff, S.},
  title = {Source separation in post nonlinear mixtures: an entropy-based algorithm},
  booktitle = {Acoustics, Speech and Signal Processing, 1998. Proceedings of the
	1998 {IEEE} International Conference on},
  year = {1998},
  volume = {4},
  pages = {2089--2092},
  owner = {Sagnik},
  shorttitle = {Source separation in post nonlinear mixtures},
  timestamp = {2012.02.23}
}

@ARTICLE{Tan1999,
  author = {Sovira Tan and Rupert C. D. Young and David M. Budgett and John D.
	Richardson and Chris R. Chatwin},
  title = {A pattern recognition Weiner filter for realistic clutter backgrounds},
  journal = {Optics Communications},
  year = {1999},
  volume = {172},
  pages = {193 - 202},
  number = {1-6},
  __markedentry = {[Sagnik]},
  doi = {DOI: 10.1016/S0030-4018(99)00599-4},
  issn = {0030-4018},
  keywords = {PACS: 42.30.Sy},
  owner = {Sagnik},
  timestamp = {2011.05.25},
  url = {http://www.sciencedirect.com/science/article/pii/S0030401899005994}
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@ARTICLE{Taware2002,
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@ARTICLE{Yeredor2000a,
  author = {Yeredor, A.},
  title = {Blind Separation of Gaussian Sources via Second-Order Statistics
	with Asymptotically Optimal Weighting},
  journal = {IEEE Signal Processing Letters},
  year = {2000},
  volume = {7},
  pages = {197-200},
  __markedentry = {[Sagnik]},
  owner = {Sagnik},
  timestamp = {2011.02.21}
}

@ARTICLE{Yeredor2000b,
  author = {A. Yeredor},
  title = {Blind Separation of Gaussian sources via second-order statatistics
	with asymptotically optimal weighting},
  journal = {IEEE Signal P},
  year = {2000},
  volume = {7(7)},
  pages = {197-200},
  __markedentry = {[Sagnik]},
  owner = {Sagnik},
  timestamp = {2011.02.16}
}

@ARTICLE{Zacklad2008,
  author = {Zacklad, Manuel and Delaunay, Tech-cico Institut Charles},
  title = {Ordre du discours : cadrage et recadrage des transactions communicationnelles
	dans les processus de changement et d ' innovation au sein des organisations},
  journal = {No\^us},
  year = {2008},
  pages = {21--22},
  number = {1999},
  owner = {Sagnik},
  shorttitle = {Ordre du discours},
  timestamp = {2012.02.23}
}

@CONFERENCE{ZeevZalevsky2004,
  author = {Zeev Zalevsky, Noam Shamir, David Mendlovic},
  title = {Blind Source Images Separation Based on Optical
	
	Fractional Fourier Transform Autocorrelation Width},
  booktitle = {Photonics},
  year = {2004},
  __markedentry = {[Sagnik]},
  owner = {Welcome},
  timestamp = {2011.02.13}
}

@ARTICLE{Zhang2005,
  author = {Zhang, K. and Chan, {L.W.}},
  title = {Extended gaussianization method for blind separation of post-nonlinear
	mixtures},
  journal = {Neural computation},
  year = {2005},
  volume = {17},
  pages = {425--452},
  number = {2},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Zhang2009,
  author = {Zhang, K. and Hyv\"arinen, A.},
  title = {On the identifiability of the post-nonlinear causal model},
  booktitle = {Proceedings of the {Twenty-Fifth} Conference on Uncertainty in Artificial
	Intelligence},
  year = {2009},
  pages = {647--655},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Zhang2008,
  author = {Zhang, K. and Hyv\"arinen, A.},
  title = {Distinguishing causes from effects using nonlinear acyclic causal
	models},
  booktitle = {{NIPS} 2008 Workshop on Causality. {URL} http://www. cs. helsinki.
	{fi/u/ahyvarin/papers/Zhang09NIPSworkshop.} pdf},
  year = {2008},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Zhang2000a,
  author = {Zhang, L. and Cichocki, A.},
  title = {Blind deconvolution of dynamical systems: A state space approach},
  journal = {Journal of Signal Processing},
  year = {2000},
  volume = {4},
  pages = {111--130},
  number = {2},
  owner = {Sagnik},
  shorttitle = {Blind deconvolution of dynamical systems},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Zhang2000c,
  author = {Zhang, L. and Cichocki, A.},
  title = {Natural gradient approach to blind deconvolution of dynamical systems},
  booktitle = {Proceeding of {ICA'2000}},
  year = {2000},
  pages = {27--32},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Zhang1999a,
  author = {Zhang, Liqing and Cichocki, Andrzej},
  title = {Blind Separation of Filtered Sources Using {State-Space} Approach},
  journal = {{ADVANCES} {IN} {NEURAL} {INFORMATION} {PROCESSING} {SYSTEMS}},
  year = {1999},
  volume = {11},
  pages = {648---654},
  owner = {Sagnik},
  timestamp = {2012.02.23},
  url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.55.5178}
}

@INPROCEEDINGS{Zhang1998,
  author = {Zhang, L. and Cichocki, A.},
  title = {Blind deconvolution/equalization using state-space models},
  booktitle = {Neural Networks for Signal Processing {VIII}, 1998. Proceedings of
	the 1998 {IEEE} Signal Processing Society Workshop},
  year = {1998},
  pages = {123--131},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Zhang2004,
  author = {Zhang, L. and Cichocki, A. and Amari, S.},
  title = {Multichannel blind deconvolution of nonminimum-phase systems using
	filter decomposition},
  journal = {Signal Processing, {IEEE} Transactions on},
  year = {2004},
  volume = {52},
  pages = {1430--1442},
  number = {5},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Zhang1999b,
  author = {Zhang, L. -q and Zhang, L. -q and Cichocki, A. and Cichocki, A. and
	Amari, S. and Amari, S.},
  title = {Multichannel Blind Deconvolution of Non-minimum Phase Systems Using
	Information Backpropagation},
  journal = {{IEEE} {TRANSACTIONS} {ON} {SIGNAL} {PROCESSING}},
  year = {1999},
  volume = {52},
  pages = {210---216},
  owner = {Sagnik},
  timestamp = {2012.02.23},
  url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.15.4414}
}

@ARTICLE{Zhang2002a,
  author = {Zhang, Q.},
  title = {Adaptive observer for multiple-input-multiple-output {(MIMO)} linear
	time-varying systems},
  journal = {Automatic Control, {IEEE} Transactions on},
  year = {2002},
  volume = {47},
  pages = {525--529},
  number = {3},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Zhang1999d,
  author = {Zhang, {L.Q.} and Amari, S. and Cichocki, A.},
  title = {Natural gradient approach to blind separation of over-and under-complete
	mixtures},
  booktitle = {In Proceeding of Independent Component Analysis and Signal Separation
	{(ICA'99}},
  year = {1999},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Zhang2001,
  author = {Zhang, {L.Q.} and Amari, {S.I.} and Cichocki, A.},
  title = {Semiparametric model and superefficiency in blind deconvolution},
  journal = {Signal processing},
  year = {2001},
  volume = {81},
  pages = {2535--2553},
  number = {12},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Zhang2002,
  author = {Zhang, {L.Q.} and Cichocki, A. and Amari, S.},
  title = {Geometrical structures of {FIR} manifold and multichannel blind deconvolution},
  journal = {The Journal of {VLSI} Signal Processing},
  year = {2002},
  volume = {31},
  pages = {31--44},
  number = {1},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Zhang2000,
  author = {Zhang, {L.Q.} and Cichocki, A. and Amari, S.},
  title = {Kalman filter and state-space approach to blind deconvolution},
  booktitle = {Neural Networks for Signal Processing X, 2000. Proceedings of the
	2000 {IEEE} Signal Processing Society Workshop},
  year = {2000},
  volume = {1},
  pages = {425--434},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Zhang1999,
  author = {Zhang, {L.Q.} and Cichocki, A. and Amari, S.},
  title = {Multichannel blind deconvolution of non-minimum phase systems using
	information backpropagation},
  booktitle = {Neural Information Processing, 1999. Proceedings. {ICONIP'99.} 6th
	International Conference on},
  year = {1999},
  volume = {1},
  pages = {210--216},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Zhang1999c,
  author = {Zhang, {L.Q.} and Cichocki, A. and Amari, S.},
  title = {Geometrical structures of {FIR} manifold and their application to
	multichannel blind deconvolution},
  booktitle = {Neural Networks for Signal Processing {IX}, 1999. Proceedings of
	the 1999 {IEEE} Signal Processing Society Workshop},
  year = {1999},
  pages = {303--312},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Zhang2000b,
  author = {Zhang, {LQ} and Amari, S. and Cichocki, A.},
  title = {Semiparametric Approach to Multichannel Blind Deconvolution of Non-minimum
	Phase Systems},
  journal = {Advances in Neural Information Processing Systems},
  year = {2000},
  volume = {12},
  pages = {363--369},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Zhou2003,
  author = {Yi Zhou and Boling Xu},
  title = {Blind source separation in frequency domain},
  journal = {Signal Processing},
  year = {2003},
  volume = {83},
  pages = {2037 - 2046},
  number = {9},
  __markedentry = {[Sagnik]},
  doi = {DOI: 10.1016/S0165-1684(03)00134-8},
  issn = {0165-1684},
  keywords = {Blind source separation},
  owner = {Sagnik},
  timestamp = {2011.02.21},
  url = {http://www.sciencedirect.com/science/article/B6V18-48PDTW9-2/2/52fce1b9dd0a1b27833ab44f9089c6e5}
}

@ARTICLE{Zibulevsky2001,
  author = {Zibulevsky, M. and Pearlmutter, {B.A.}},
  title = {Blind source separation by sparse decomposition in a signal dictionary},
  journal = {Neural computation},
  year = {2001},
  volume = {13},
  pages = {863--882},
  number = {4},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Ziehe2003,
  author = {Ziehe, A. and Kawanabe, M. and Harmeling, S. and M\"uller, {K.R.}},
  title = {Blind separation of post-nonlinear mixtures using linearizing transformations
	and temporal decorrelation},
  journal = {The Journal of Machine Learning Research},
  year = {2003},
  volume = {4},
  pages = {1319--1338},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@INPROCEEDINGS{Ziehe2001,
  author = {Ziehe, A. and Kawanabe, M. and Harmeling, S. and M\"uller, {K.R.}},
  title = {Separation of post-nonlinear mixtures using {ACE} and temporal decorrelation},
  booktitle = {Proc. Int. Workshop on Independent Component Analysis and Blind Signal
	Separation {(ICA2001)}},
  year = {2001},
  pages = {433--438},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@ARTICLE{Ziehe2000,
  author = {Ziehe, A. and Muller, K. {-R} and Nolte, G. and Mackert, B. {-M}
	and Curio, G.},
  title = {Artifact reduction in magnetoneurography based on time-delayed second-order
	correlations},
  journal = {{IEEE} Transactions on Biomedical Engineering},
  year = {2000},
  volume = {47},
  pages = {75--87},
  number = {1},
  month = jan,
  abstract = {Artifacts in magnetoneurography data due to endogenous biological
	noise sources, like the cardiac signal, can be four orders of magnitude
	higher than the signal of interest. Therefore, it is important to
	establish effective artifact reduction methods. We propose a blind
	source separation algorithm using only second-order temporal correlations
	for cleaning biomagnetic measurements of evoked responses in the
	peripheral nervous system. The algorithm showed its efficiency by
	eliminating disturbances originating from biological and technical
	noise sources and successfully extracting the signal of interest.
	This yields a significant improvement of the neuro-magnetic source
	analysis},
  doi = {10.1109/10.817622},
  issn = {0018-9294},
  keywords = {adaptive signal processing, artifact reduction, Biological information
	theory, biomagnetic measurements, Biomagnetics, biomagnetism, Biomedical
	imaging, Biomedical measurements, Blind source separation, blind
	source separation algorithm, cardiac signal, decorrelation, endogenous
	biological noise sources, evoked responses, Higher order statistics,
	higher-order moments, Independent component analysis, interference
	suppression, linear algebra, Magnetic analysis, Magnetic separation,
	magnetoneurography, medical signal processing, Nervous system, neuro-magnetic
	source analysis, neurophysiology, peripheral nervous system, second-order
	temporal correlations, Signal processing algorithms, time-delayed
	second-order correlations},
  owner = {Sagnik},
  timestamp = {2012.02.23}
}

@BOOK{Widrow1996,
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  timestamp = {2012.02.23}
}

@MISC{,
  title = {Source separation - Wikipedia, the free encyclopedia},
  howpublished = {{http://en.wikipedia.org/wiki/Source\_separation}},
  owner = {Sagnik},
  timestamp = {2012.02.23},
  url = {http://en.wikipedia.org/wiki/Source_separation}
}

@MISC{,
  title = {Degenerate Unmixing Estimation Technique for Undetermined Blind Signal
	Separation},
  howpublished = {http://www.vocal.com/blind\_signal\_separation/underdetermined.html},
  owner = {Sagnik},
  timestamp = {2012.02.23},
  url = {http://www.vocal.com/blind_signal_separation/underdetermined.html}
}

@MISC{,
  title = {Introduction to Blind Source Separation},
  howpublished = {http://perso.univ-rennes1.fr/laurent.albera/alberasiteweb/bss.html},
  owner = {Sagnik},
  timestamp = {2012.02.23},
  url = {http://perso.univ-rennes1.fr/laurent.albera/alberasiteweb/bss.html}
}

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